Note: Descriptions are shown in the official language in which they were submitted.
ELECTRICAL DATA PROCESSING SYSTEM FOR DETERMINING A
NAVIGATION ROUTE BASED ON THE LOCATION OF A VEHICLE AND
GENERATING A RECOMMENDATION FOR A VEHICLE MANEUVER
CROSS-REFERENCE SECTION
[01] This application claims priority to U.S. Patent Application Serial
No. 15/249,597 filed
August 29, 2016, and entitled "Electrical Data Processing System for
Determining a
Navigation Route Based on the Location of a Vehicle and Generating a
Recommendation for a Vehicle Maneuver". This application also claims priority
to both
U.S. Patent Application Serial No. 15/249,556, filed August 29, 2016, and
entitled,
"Electrical Data Processing System for Monitoring or Affecting Movement of a
Vehicle
Using a Traffic Device", and U.S. Patent Application Serial No. 15/249,536,
filed
August 29, 2016, and entitled, "Electrical Data Processing System for
Determining
Status of Traffic Device and Vehicle Movement".
TECHNICAL FIELD
[02] Aspects of the disclosure generally relate to an electrical data
processing system for
determining the status of a traffic device and vehicle movement, monitoring or
affecting
movement of a vehicle using a traffic device, and/or determining a navigation
route
based on the location of a vehicle and/or generating a recommendation for a
vehicle
maneuver.
BACKGROUND
[03] Traffic accidents and other unsafe conditions on or affecting roads is
surprisingly
common. Drivers, pedestrians, bicyclists, and other parties often rely on
their own
abilities to avoid accidents and unsafe conditions. However, conditions for
these
individuals may be made even safer using certain traffic infrastructure,
vehicle
capabilities, and mobile device capabilities, many of which currently are not
being
utilized.
SUMMARY
[04] The following presents a simplified summary in order to provide a basic
understanding
of some aspects of the disclosure. The summary is not an extensive overview of
the
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disclosure. It is neither intended to identify key or critical elements of the
disclosure
nor to delineate the scope of the disclosure. The following summary merely
presents
some concepts of the disclosure in a simplified form as a prelude to the
description
below.
[05] Aspects of the disclosure relate to a system comprising a traffic device
having a traffic
device computer, one or more traffic signals, and/or a transceiver. The system
may
comprise first memory storing computer-executable instructions that, when
executed
by the traffic device computer, cause the traffic device to transmit, via the
transceiver
and to a vehicle and infrastructure computing device, information indicative
of a status
of the one or more traffic signals. The vehicle and infrastructure computing
device may
comprise a vehicle and infrastructure control computer and/or second memory
storing
computer-executable instructions that, when executed by the vehicle and
infrastructure
control computer, cause the vehicle and infrastructure computing device to
receive,
from the traffic device, the information indicative of the status of the one
or more traffic
signals. The computing device may determine that the information indicative of
the
status of the one or more traffic signals indicates that the one or more
traffic signals of
the traffic device switched from a red light to a green light and a time that
the one or
more traffic signals of the traffic device switched from the red light to the
green light.
In response to determining that the one or more traffic signals of the traffic
device
switched from the red light to the green light, the computing device may
determine an
amount of time between the time that the one or more traffic signals of the
traffic device
switched from the red light to the green light and a time that a vehicle at a
location of
the traffic device moved. In response to determining that the amount of time
exceeds
a threshold amount of time, the computing device may determine that a driver
of the
vehicle is distracted.
[06] In some aspects, the system may comprise a traffic camera. The vehicle
and
infrastructure computing device may receive, from the traffic camera, one or
more
images of the vehicle captured by the traffic camera. Based on the one or more
images
of the vehicle captured by the traffic camera, the computing device may
determine the
time that the vehicle at the location of the traffic device moved.
Additionally or
alternatively, the system may comprise a mobile device having one or more of a
position sensor, speed sensor, or acceleration sensor. The computing device
may
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receive, from the mobile device or the vehicle, data indicative of one or more
of a
position, speed, or acceleration of the vehicle. Based on the data indicative
of one or
more of the position, speed, or acceleration of the vehicle, the computing
device may
determine the time that the vehicle at the location of the traffic device
moved.
[07] In some aspects, the vehicle and infrastructure computing device may
determine that
the vehicle is at the location of the traffic device and that the one or more
traffic signals
of the traffic device is not red. In response to determining that the vehicle
is at the
location of the traffic device and that the one or more traffic signals of the
traffic device
is not red, the computing device may send an instruction to one or more mobile
device
of the driver to prevent driver interaction with the mobile device while the
one or more
traffic signals of the traffic device is not red. The instruction may be
configured to
disable one or more applications of the mobile device, such as a messaging
application.
[08] In some aspects, the vehicle and infrastructure computing device may
determine that
the vehicle is at the location of the traffic device and that the one or more
traffic signals
of the traffic device is red. In response to determining that the vehicle is
at the location
of the traffic device and that the one or more traffic signals of the traffic
device is red,
the computing device may send an instruction to one or more mobile device of
the
driver to enable use of the mobile device while the one or more traffic
signals of the
traffic device is red. The vehicle and infrastructure computing device may
determine
that the one or more traffic signals of the traffic device switched from red
to green. In
response to determining that the one or more traffic signals of the traffic
device
switched from red to green, the computing device may send an instruction to
the one or
more mobile device of the driver to prevent driver interaction with the mobile
device
while the one or more traffic signals of the traffic device is green.
[09] In some aspects, the vehicle and infrastructure computing device may
adjust a risk score
for the driver based on determining that the driver of the vehicle is
distracted.
Additionally or alternatively, the vehicle and infrastructure computing device
may, in
response to determining that the one or more traffic signals of the traffic
device has
switched from the red light to the green light, send an instruction to one or
more mobile
device of the driver or to the vehicle to display an indication to the driver
that the one
or more traffic signals is a green light. The instruction may cause the mobile
device to
audibly or visually notify the driver that the one or more traffic signals is
green.
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[10] Aspects of the disclosure relate to a system comprising an event data
source having a
processor and/or a transceiver. The system may comprise first memory storing
computer-executable instructions that, when executed by the processor, cause
the event
data source to transmit, via the transceiver and to a vehicle and
infrastructure computing
device, information indicative of an event affecting a portion of road. The
vehicle and
infrastructure computing device may comprise a vehicle and infrastructure
control
computer and/or second memory storing computer-executable instructions that,
when
executed by the vehicle and infrastructure control computer, cause the vehicle
and
infrastructure computing device to receive, from the event data source, the
information
indicative of the event affecting the portion of road. The computing device
may
determine one or more traffic devices associated with the portion of road and
configured
to control traffic for the portion of road. Based on the information
indicative of the
event affecting the portion of road, the computing device may send, to the one
or more
traffic devices associated with the portion of road, instructions to change
one or more
characteristics of the one or more traffic devices.
[11] In some aspects, the one or more traffic devices may comprise a traffic
light having a
plurality of lights. Moreover, the one or more characteristics of the traffic
light may
comprise a timing of the plurality of lights. Additionally or alternatively,
the one or
more traffic devices may comprise a speed limit display. The one or more
characteristics of the speed limit display may comprise a speed limit
displayed on the
speed limit display.
[12] In some aspects, the information indicative of the event affecting the
portion of road
may comprise time information and information indicative of an estimate of a
number
of pedestrians associated with the event affecting the portion of road. The
information
indicative of the event may be accessible from an electronic calendar. The
portion of
road may comprise an intersection. Moreover, the information indicative of the
event
affecting the intersection may indicate that a number of pedestrians at the
intersection
will exceed a threshold number of pedestrians.
[13] In some aspects, the event may comprise an accident involving one or more
vehicles
affecting traffic flow through the portion of road. The one or more traffic
devices may
comprise one or more of a traffic light or a speed limit display. The
instructions to
change one or more characteristics of the one or more traffic devices may
comprise one
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or more of instructions to increase a frequency of red lights at the traffic
light or
instructions to decrease a speed limit displayed on the speed limit display.
[14] In some aspects, based on the information indicative of the event
affecting the portion
of road, the computing device may send, to one or more autonomous vehicles,
instructions to take one or more actions in response to the event. The
instructions to
take one or more actions may comprise an instruction for the autonomous
vehicle to
apply brakes, an instruction for the autonomous vehicle to slow down, or an
instruction
for the autonomous vehicle to speed up.
[15] In some aspects, the system may comprise a pedestrian barrier associated
with the
portion of road. The vehicle and infrastructure computing device may, based on
the
information indicative of the event affecting the portion of road, send, to
the pedestrian
barrier, instructions to activate the pedestrian barrier to prevent
pedestrians from
entering the portion of road. Additionally or alternatively, the vehicle and
infrastructure
computing device may, based on the information indicative of the event
affecting the
portion of road, send, to a mobile device of a pedestrian located proximate
the portion
of road, instructions for the mobile device to audibly or visually notify the
pedestrian
of the event affecting the portion of road.
[16] Aspects of the disclosure relate to a method comprising determining,
based on sensor
data received from a location sensor of a mobile device or a vehicle, a
location of the
vehicle. A computing device may determine a navigation route for navigating
the
vehicle from the location to a destination, and the navigation route may
comprise a
plurality of intersections. The computing device may determine a plurality of
potential
maneuvers at a first intersection of the plurality of intersections. The
computing device
may also determine, based on one or more factors, a navigation score for each
of the
plurality of potential maneuvers at the first intersection. Based on the
navigation score
for each of the plurality of potential maneuvers, the computing device may
select a
maneuver from the plurality of potential maneuvers to recommend for the
vehicle.
[17] In some aspects, the computing device may be at a location remote from
the location
of the vehicle. The method may comprise wireless transmitting, by the
computing
device, the selected maneuver to a navigation application associated with one
or more
of the mobile device or the vehicle. Additionally or alternatively, the one or
more
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factors may comprise a level of autonomy of the vehicle. Determining the
navigation
score for each of the plurality of potential maneuvers may comprise
determining the
navigation score for each of the plurality of potential maneuvers based on the
level of
autonomy of the vehicle.
[18] In some aspects, the vehicle may comprise an autonomous vehicle, and the
method may
further comprise sending the selected maneuver to the autonomous vehicle.
Additionally or alternatively, the vehicle may have a plurality of autonomous
features
activated. The computing device may receive, from one or more of the vehicle
or
mobile device, data indicating that the vehicle is approaching the first
intersection. In
response to receiving the data indicating that the vehicle is approaching the
first
intersection, an instruction to deactivate one or more of the plurality of
autonomous
features may be sent to the vehicle. One or more factors may comprise whether
the
vehicle is autonomous, and the method may further comprise determining, by the
computing device, whether the vehicle is autonomous. Selecting the maneuver
may
comprise selecting a first maneuver to recommend if the vehicle is autonomous
and
selecting a second maneuver to recommend if the vehicle is not autonomous.
[19] In some aspects, the plurality of potential maneuvers at the first
intersection may
comprise at least two of a right turn at the first intersection, a left turn
at the first
intersection, a U turn at the first intersection, and proceeding straight
through the first
intersection. In some aspects, the computing device may determine an
intersection
score for each of the plurality of intersections based on one or more of a
complexity of
the intersection, a number of accidents at the intersection, weather, or
traffic congestion.
[20] Other features and advantages of the disclosure will be apparent from the
additional
description provided herein.
BRIEF DESCRIPTION OF THE DRAWINGS
[21] A more complete understanding of the present invention and the advantages
thereof
may be acquired by referring to the following description in consideration of
the
accompanying drawings, in which like reference numbers indicate like features,
and
wherein:
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[22] FIG. 1 is a diagram illustrating various example components of a vehicle
and
infrastructure control system according to one or more aspects of the
disclosure.
[23] FIG. 2 illustrates an example network environment and computing systems
that may be
used to implement aspects of the disclosure.
[24] FIGS. 3A-B are flow diagrams illustrating example methods of determining
status of a
traffic device and vehicle movement according to one or more aspects of the
disclosure.
[25] FIG. 4 is a flow diagram illustrating an example method of monitoring or
affecting
movement of a vehicle using a traffic device according to one or more aspects
of the
disclosure.
[26] FIG. 5 is a flow diagram illustrating an example method of determining a
navigation
route based on the location of a vehicle and generating a recommendation for a
vehicle
maneuver according to one or more aspects of the disclosure.
[27] FIG. 6 is a flow diagram illustrating an example method of sending
instructions to
and/or controlling a device in a vehicle based on the status of a traffic
device according
to one or more aspects of the disclosure.
[28] FIGS. 7A-B are flow diagrams illustrating example methods of sending
instructions to
and/or controlling a traffic device and/or mobile device to control the flow
of
pedestrians, bicyclists, etc. through an intersection according to one or more
aspects of
the disclosure.
DETAILED DESCRIPTION
[29] In the following description of the various embodiments, reference is
made to the
accompanying drawings, which form a part hereof, and in which is shown by way
of
illustration, various embodiments of the disclosure that may be practiced. It
is to be
understood that other embodiments may be utilized.
[30] As will be appreciated by one of skill in the art upon reading the
following disclosure,
various aspects described herein may be embodied as a method, a computer
system, or
a computer program product. Aspects may take the form of a computing device
configured to perform specified actions. Furthermore, such aspects may take
the form
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of a computer program product stored by one or more computer-readable storage
media
having computer-readable program code, or instructions, embodied in or on the
storage
media. Any suitable computer readable storage media may be utilized, including
hard
disks, CD-ROMs, optical storage devices, magnetic storage devices, and/or any
combination thereof. In addition, various signals representing data or events
as
described herein may be transferred between a source and a destination in the
form of
electromagnetic waves traveling through signal-conducting media such as metal
wires,
optical fibers, and/or wireless transmission media (e.g., air and/or space).
[31] FIG. 1 is a diagram illustrating various example components of a vehicle
and
infrastructure control system 100 according to one or more aspects of the
disclosure.
The vehicle and infrastructure control system 100 may include a vehicle 110,
other
vehicles (not illustrated in FIG. 1), one or more traffic devices (e.g.,
traffic or roadway
infrastructure devices) in a traffic device network or system 120, one or more
mobile
devices 130 (e.g., a mobile device of a pedestrian or a bicyclist), one or
more bicycles
135, one or more buildings 125, one or more weather data source 140, one or
more
event data source 145, one or more map data source 170, one or more historical
driver
or vehicle data source 175, one or more historical traffic or infrastructure
data source
180, one or more broadcast and/or emergency receiver 185, a vehicle and
infrastructure
control server 150, and additional related components. Each component of the
vehicle
and infrastructure control system 100 may include a computing device (or
system)
having some or all of the following structural components.
[32] For example, the vehicle and infrastructure control computer or computing
device 151
may have a processor for controlling overall operation of the computing device
151 and
its associated components, including RAM, ROM, input/output module, and
memory.
The computing device 151, along with one or more additional devices (e.g.,
vehicle
110, traffic device in the traffic device system or network 120, mobile device
130,
bicycle 135, building 125, weather data source 140, etc.), may correspond to
any of
multiple systems or devices, such as vehicle and infrastructure control
computing
devices or systems, configured as described herein for determining the status
of a traffic
device and vehicle movement, monitoring or affecting movement of a vehicle
using a
traffic device, or determining a navigation route based on the location of a
vehicle and
generating a recommendation for a vehicle maneuver.
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[33] Sensor data can include data collected from mobile devices (e.g.,
a driver's mobile
phone, a passenger's mobile phone, a pedestrian's mobile phone), vehicle
sensors, on-
board diagnostic (OBD) systems, sensors on traffic devices (e.g., traffic
cameras, etc.),
off the shelf devices, or any other devices as will be described in further
detail below.
Sensor data may refer to information pertaining to one or more actions or
events
performed or observed by a vehicle, a pedestrian, traffic devices, or any
other devices
and can include aspects of information identified or determined from data
collected
from a vehicle, a stationary device, or a mobile device. Sensor data can
include, for
example, location data, speed or velocity data, acceleration data, braking
data, turning
or swerving data, image data, presence data, time data, direction data, mobile
device
orientation data, rotation/gyroscopic data, weather data, vehicle condition
data, and the
like.
[34] The vehicle and infrastructure control computer 151 may include an Input
/ Output
(I/O) module having a microphone, keypad, touch screen, and/or stylus through
which
a user of the computing device 151 may provide input, and may also include one
or
more of a speaker for providing audio input/output and a video display device
for
providing textual, audiovisual and/or graphical output. Software may be stored
within
the memory of the vehicle and infrastructure control computer and/or other
storage to
provide instructions to its processor for enabling device 151 to perform
various
functions. For example, the computing device's memory may store software used
by
the device 151, such as an operating system, application programs, and an
associated
internal or external database 151. The memory unit may include one or more of
volatile
and/or non-volatile computer memory to store computer-executable instructions,
data,
and/or other information. The processor of the computer 151 and its associated
components may allow the vehicle and infrastructure control computer 151 to
execute
a series of computer-readable instructions to determine the status of a
traffic device and
vehicle movement, monitor or affect movement of a vehicle using a traffic
device, or
determine a navigation route based on the location of a vehicle and generating
a
recommendation for a vehicle maneuver. One or more application programs used
by
the vehicle and infrastructure control computing device 151 may include
computer
executable instructions for determining the status of a traffic device and
vehicle
movement, monitoring or affecting movement of a vehicle using a traffic
device, or
determining a navigation route based on the location of a vehicle and
generating a
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recommendation for a vehicle maneuver and performing other related functions
as
described herein.
[35] The vehicle and infrastructure control computing device 151 may operate
in a
networked environment supporting connections to one or more remote computers,
such
as various other terminals / devices (e.g., terminal 160, which may include a
display).
The vehicle and infrastructure control computing device 151, and the related
terminals
/ devices, may communicate with devices installed in vehicles, mobile devices
that may
travel within vehicles, or devices outside of vehicles that are configured to
receive and
process vehicle data, pedestrian data, and other sensor data. Thus, the
vehicle and
infrastructure control computing device 151 and its associated terminals /
devices may
each include personal computers (e.g., laptop, desktop, or tablet computers)
and/or
servers (e.g., web servers, database servers) and may communicate with vehicle-
based
devices (e.g., on-board vehicle computers, short-range vehicle communication
systems,
sensor and telematics devices), or mobile communication devices (e.g., mobile
phones,
portable computing devices, and the like). The vehicle and infrastructure
control server
150 (and/or its components) may be able to indicate its health to other
systems (and/or
their components) interfacing with the server 150.
[36] The devices illustrated in system 100 may communicate via network
connections
depicted such as a local area network (LAN) and a wide area network (WAN), and
a
wireless telecommunications network, but may also include other networks. When
used in a LAN networking environment, the vehicle and infrastructure control
computing device 151 may be connected to the LAN through a network interface
or
adapter. When used in a WAN networking environment, the device 151 may include
a
modem or other means for establishing communications over the WAN, such as a
network (e.g., the Internet). When used in a wireless telecommunications
network, the
device 151 may include one or more transceivers, digital signal processors,
and
additional circuitry and software for communicating with wireless computing
devices
(e.g., mobile phones, short-range vehicle communication systems, vehicle
sensing and
telematics devices) via one or more network devices (e.g., base transceiver
stations) in
the wireless network. It will be appreciated that the network connections
shown and
described above are illustrative and other means of establishing a
communications link
between the computers may be used. The existence of any of various network
protocols
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such as TCP/IP, Ethernet , FTP, HTTP and the like, and of various wireless
communication technologies such as GSM, CDMA, Wi-FiO, and WiMAXO, is
presumed, and the various computing devices and vehicle and infrastructure
control
system components described herein may be configured to communicate using any
of
these network protocols or technologies. The communications between the
devices
illustrated in system 100 (including communications between the vehicle and
infrastructure control server 150 and other devices) may be secured, such as
via
Transport Layer Security (TLS), Secure Sockets Layer (SSL), or any other
cryptographic protocols for securing communications.
[37] The vehicle 110 may be, for example, an automobile, motorcycle, scooter,
bus,
recreational vehicle, boat, or other vehicle for which sensor data may be
collected and
analyzed. A mobile computing device 116 within the vehicle 110 may be used to
collect
sensor data (e.g., via sensors 118) and/or to receive sensor data from the
vehicle 110
(e.g., via vehicle sensors 119). The mobile device 116 may process the data to
detect
one or more conditions involving the vehicle 110 and/or transmit the sensor
data to the
vehicle and infrastructure control server 150 or other external computing
devices.
Mobile computing device 116 may be, for example, mobile phones, personal
digital
assistants (PDAs), tablet computers, laptop computers, smartwatches, and other
devices
that may be carried by drivers or passengers inside or outside of the vehicle
110.
[38] The mobile computing device 116 may contain some or all of the
hardware/software
components of the computing device 151 described above. Software applications
may
be installed on and execute on the mobile device 116. The software
applications may
be configured to receive sensor data from internal sensors 118, such as
acceleration,
velocity, location, and the like and/or communicate with vehicle sensors 119
or other
vehicle communication systems to sense or receive sensor data. For example,
mobile
device 116 equipped with Global Positioning System (GPS) functionality may
determine vehicle location, speed, direction and other basic driving data
without
needing to communicate with vehicle sensors or external vehicle systems. The
mobile
software application may also receive sensor data from a wearable device, such
as a
smartwatch or a fitness band. In other examples, the software application on
the mobile
device 116 may be configured to receive some or all of the sensed data
collected by
sensors 119 of the vehicle 110.
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[39] When mobile computing device 116 within the vehicle 110 is used to sense
vehicle
data, the mobile computing device 116 may store, analyze, and/or transmit the
vehicle
data to one or more other computing devices. For example, mobile device 116
may
transmit vehicle data directly to vehicle and infrastructure control server
150, and thus
may be used instead of sensors or communication systems of the vehicle 110.
[40] The mobile device 116 may include various sensors 118 capable of
detecting and
recording conditions at and operational parameters of the vehicle 110 if the
mobile
device 116 is inside the vehicle. The sensors 118 may be used to sense, for
example,
the location of the mobile device 116, such as the GPS coordinates (e.g.,
latitude and
longitude). The location of the mobile device 116 may also be determined based
on
wireless networks the mobile device has connected to, such as Wi-Fi0 networks,
cellular networks, and the like.
[41] The sensors 118 of the mobile device 116, such as a GPS and/or a compass,
may sense
the speed and/or direction at which the mobile device 116 and accordingly
vehicle 110
is traveling. An accelerometer of the mobile device 116 may sense the
acceleration of
the mobile device. A gyroscope may be used to determine the orientation of the
mobile
device. The gyroscope may also be used to measure the speed of rotation of the
mobile
device 116. A magnetometer may be used to measure the strength and direction
of the
magnetic field relative to the mobile device. The sensors 118 may comprise an
image
sensor (e.g., a camera), an audio sensor (e.g., a microphone), a presence
sensor, etc.
The sensors 118 previously described are exemplary, and the mobile device 116
may
include any other sensors used for vehicle and infrastructure control.
[42] The data collected by the mobile device 116 may be stored and/or analyzed
within the
mobile device 116. The processing components of the mobile computing device
116
may be used to analyze sensor data, determine the status of a traffic device
and vehicle
movement, monitor or affect movement of a vehicle using a traffic device, or
determine
a navigation route based on the location of a vehicle and generate a
recommendation
for a vehicle maneuver. Additionally or alternatively, the mobile device 116
may
transmit, via a wired or wireless transmission network, the data to one or
more external
devices for storage or analysis, such as vehicle computer 114 or vehicle and
infrastructure control server 150. In other words, mobile computing device 116
may
be used in conjunction with, or in place of, the vehicle computer 114 or
vehicle and
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infrastructure control server 150 to determine how to control vehicles and
infrastructure.
[43] The vehicle computer 114 of the vehicle 110 may contain some or all of
the
hardware/software components of the computing device 151 described above. The
vehicle computer 114 may receive sensor data from the mobile device 116 and/or
from
sensors 119 built into the vehicle 110. For example, vehicle computer 114 may
receive
telematics data from the mobile device 116 or a telematics device in the
vehicle 110
when the vehicle 110 is approaching an intersection or another portion of a
road, such
as when the vehicle 110 is a threshold distance from the intersection or other
portion of
road. Sensors 119 may include, for example, telematics devices integrated with
the
vehicle and/or aftermarket telematics devices. The telematics devices may be
used to
track location (e.g., via a GPS location point or GPS trail), vehicle
diagnostics, speed,
acceleration, and the like. The telematics devices may comprise a microphone
used to
collect audio data. In some aspects, the aftermarket telematics devices may be
connected to the vehicle by wire, such as via the vehicle's OBD port.
Aftermarket
devices may additionally or alternatively connect to the vehicle (or other
devices within
the vehicle, such as a mobile device) wirelessly.
[44] The vehicle computer 114 may act as a gateway device between the mobile
device 116
and the vehicle and infrastructure control server 150. For example, the
vehicle
computer 114 may receive sensor data from the mobile device 116 and forward
the
received data to the vehicle and infrastructure control server 150. The
vehicle 110 may
include a short-range communication system 112, which will be described in
further
detail below. While one vehicle is illustrated in Figure 1, any number of
vehicles (and
their computing devices, sensors, and mobile devices) may be used for vehicle
and
infrastructure control. Moreover, sensor data may be collected from one or
more
moving vehicles, one or more parked vehicles, or a combination of moving and
parked
vehicles.
[45] The transceiver 112 may comprise or be part of a short-range
communication system,
such as a vehicle-based data transmission system configured to transmit
vehicle data to
other nearby vehicles, and to receive vehicle data from other nearby vehicles.
In some
examples, the transceiver 112 may use the dedicated short-range communications
(DSRC) protocols and standards to perform wireless communications between
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vehicles. In the United States, 75 MHz in the 5.850-5.925 GHz band have been
allocated for DSRC systems and applications, and various other DSRC
allocations have
been defined in other countries and jurisdictions. However, the communication
system
112 need not use DSRC, and may be implemented using other short-range wireless
protocols in other examples, such as WLAN communication protocols (e.g., IEEE
802.11), Bluetooth0 (e.g., IEEE 802.15.1), or one or more of the Communication
Access for Land Mobiles (CALM) wireless communication protocols and air
interfaces.
[46] The vehicle-to-vehicle (V2V) transmissions between the communication
system 112
and another vehicle's communication system may be sent via DSRC , Bluetooth0,
satellite, GSM infrared, IEEE 802.11, WiMAXO, RFIDO, and/or any suitable
wireless
communication media, standards, and protocols. In
certain systems, the
communication system 112 may include specialized hardware installed in vehicle
110
(e.g., transceivers, antennas, etc.), while in other examples the
communication system
112 may be implemented using existing vehicle hardware components (e.g., radio
and
satellite equipment, navigation computers) or may be implemented by software
running
on the mobile device 116 of drivers and passengers within the vehicle 110.
[47] The range of V2V communications between vehicle communication systems may
depend on the wireless communication standards and protocols used, the
transmission
/ reception hardware (e.g., transceivers, power sources, antennas), and other
factors.
Short-range V2V communications may range from just a few feet to many miles.
V2V
communications also may include vehicle-to-infrastructure (V2I) or vehicle-to-
everything (V2X) communications, such as transmissions from vehicles to non-
vehicle
receiving devices, for example, toll booths, rail road crossings, road-side
traffic
monitoring devices, or generally to one or more traffic device in a traffic
device system
or network 120. Certain V2V communication systems may periodically broadcast
data
from a vehicle 110 to any other vehicle, or other infrastructure device
capable of
receiving the communication, within the range of the vehicle's transmission
capabilities. For example, a vehicle 110 may periodically broadcast (e.g.,
every 0.1
second, every 0.5 seconds, every second, every 5 seconds, etc.) certain
vehicle data via
its short-range communication system 112, regardless of whether or not any
other
vehicles or reception devices are in range. In other examples, a vehicle
communication
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system 112 may first detect nearby vehicles and receiving devices, and may
initialize
communication with each by performing a handshaking transaction before
beginning
to transmit its vehicle data to the other vehicles and/or devices. The mobile
device 116
may similarly broadcast data to a vehicle, infrastructure, another mobile
device, or any
other computing devices periodically or when the mobile device 116 detects
other
vehicles or receiving devices.
[48] The types of vehicle data transmitted by the vehicle 110 may depend on
the protocols
and standards used for the V2V communication, the range of communications,
whether
to initiate vehicle and infrastructure control, and other factors. In certain
examples, the
vehicle 110 may periodically broadcast corresponding sets of similar vehicle
driving
data, such as the location (which may include an absolute location in GPS
coordinates
or other coordinate systems, and/or a relative location with respect to
another vehicle
or a fixed point), speed, and direction of travel. In certain examples, the
nodes in a
V2V communication system (e.g., vehicles and other reception devices) may use
internal clocks with synchronized time signals, and may send transmission
times within
V2V communications, so that the receiver may calculate its distance from the
transmitting node based on the difference between the transmission time and
the
reception time. The state or usage of the vehicle's 110 controls and
instruments may
also be transmitted, for example, whether the vehicle is accelerating,
braking, turning,
and by how much, and/or which of the vehicle's instruments are currently
activated by
the driver (e.g., head lights, turn signals, hazard lights, cruise control, 4-
wheel drive,
traction control, windshield wipers, etc.). Vehicle warnings such as detection
by the
vehicle's 110 internal systems that the vehicle is skidding, that an impact
has occurred,
or that the vehicle's airbags have been deployed, also may be transmitted in
V2V
communications.
[49] The mobile computing device 116 may be used instead of, or in conjunction
with, the
communication system 112. For example, the mobile device 116 may communicate
directly with the other vehicle or directly with another mobile device, which
may be
inside or outside of the other vehicle. Additionally or alternatively, the
other vehicle
may communicate location information to vehicle 110, and vehicle 110 may in
turn
communicate this location information to the mobile device 116. Any data
collected
by any vehicle sensor or mobile device 116 sensor may be transmitted via V2V
or other
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communication to other nearby vehicles, mobile devices, or infrastructure
devices
receiving V2V communications from communication system 112 or communications
directly from mobile device 116. Further, additional vehicle driving data not
from the
vehicle's sensors (e.g., vehicle make/model/year information, driver
information, etc.)
may be collected from other data sources, such as a driver's or passenger's
mobile
device 116, vehicle and infrastructure control server 150, and/or another
external
computer system, and transmitted using V2V communications to nearby vehicles
and
other transmitting and receiving devices using communication system 112.
[50] The system 100 may also include a traffic device 120A, containing some or
all of the
hardware/software components of the computing device 151 described above. The
traffic device 120A may comprise one or more sensors 122, such as image
sensors (e.g.,
cameras or other sensors used to detect the presence and/or proximity of one
or more
vehicles, bicycles, pedestrians, and the like), location sensors (e.g., GPS or
other
location sensors), audio sensors (e.g., microphones, which may be used to
detect car
crashes, approaching emergency vehicles, and the like), etc. The traffic
device 120A
may also have time data, such as from a clock, and may transmit the time data
to the
vehicle and infrastructure control server 150 with or separate from the sensor
data. The
vehicle and infrastructure control server 150 may also receive time data from
any other
sources, such as an atomic clock.
[51] The traffic device 120A may comprise a traffic light 120B (e.g., at an
intersection of
roads), which may determine and store time and status data, such as whether
the traffic
light was red, yellow, or green at each point in time. The traffic light 120B
may have
any of the sensors described herein, including image sensors, location
sensors, audio
sensors, and the like. The traffic device 120A may also comprise, for example,
a traffic
camera 120C on the road (e.g., a standalone camera, a camera integrated in a
traffic
light, and the like) or a traffic camera in the air (e.g., a camera on a
drone, a helicopter,
an airplane, or any other aerial vehicle, whether manned or unmanned). The
traffic
camera 120C may be used to capture images of vehicles, bicycles, and/or
pedestrians
passing the traffic camera. The traffic device 120A may also comprise a
traffic counter,
such as magnetic strips, configured to count traffic flow (e.g., number and/or
frequency
of vehicles, bicycles, pedestrians, etc. passing by the traffic device 120A).
The traffic
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flow data may be used to determine the ratio of accidents to the number of
vehicles
passing by the traffic device 120A, such as passing through a traffic light
120B.
[52] The traffic device 120A may include sensors to detect the condition of a
segment of
road, such as water (e.g., standing water or water flow), ice (e.g., ice
buildup, the
presence of black ice, etc.), precipitation (e.g., the amount of snow on the
road or the
start of snowfall or rainfall), and the like. With (or separately from) the
condition
information, the traffic device 120A may also transmit what type of
infrastructure it is,
such as a bridge, a ramp, a hill, an intersection, etc. The traffic device
120A may
comprise any other type of traffic or street infrastructure, such as a
tollbooth, a
streetlight, or pedestrian/bicycle crosswalk infrastructure. For example, the
streetlight
may communicate with the vehicle and infrastructure control server 150 or any
other
computing devices if the streetlight is out or dim. As another example, the
pedestrian/bicycle crosswalk infrastructure may include a button that the
pedestrian or
bicyclist can press to cross the street, and a press of the button may
indicate the presence
of a pedestrian or bicyclist. The pedestrian/bicycle crosswalk infrastructure
may also
include a barrier 120D, which may prevent or allow pedestrians or bicycles
from
crossing the street (e.g., by raising or lowing the barrier 120D). The traffic
device 120A
may comprise a display device 120E (e.g., an LCD or LED display device)
configured
to display, for example, the speed limit, messages, or any other graphics or
texts. The
traffic device 120A may also comprise a transceiver 124 for transmitting and
receiving
data, and a traffic computer 126 used to process data and to determine data to
send to
the vehicle and infrastructure control server 150.
[53] The system 100 may include one or more mobile computing device 130, which
may be
similar to mobile computing device 116, except that the mobile computing
device 130
may be outside of a vehicle (e.g., a pedestrian's mobile device, a bicyclist's
135 mobile
device, or any other mobile device). The mobile computing device 130 may
contain
some or all of the hardware/software components of the computing device 151
described above. Software applications executing on the mobile device 130 may
be
configured to receive sensor data from sensors 132, such as acceleration,
velocity,
location, and the like. The location of the mobile device 130 may be
determined based
on wireless networks the mobile device has connected to, such as Wi-Fi0
networks,
cellular networks, GPS, and the like. As described above, the sensors 132 may
also
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comprise a compass, an accelerometer, a gyroscope, a magnetometer, or any
other type
of sensor. The mobile computing device 130 may also comprise other mobile
devices
or accessories, such as a wearable (e.g., a smartwatch).
[54] The system 100 may comprise one or more buildings 125 used to accommodate
large
numbers of people, such as schools, restaurants, stadiums, office buildings,
concert
halls, auditoriums, and the like. Each building 125 may have one or more of
the sensors
described above for the traffic device 120, or one or more of the sensors may
be located
close to the building 125, such as in front of or behind the building 125. For
example,
the building 125 may include a camera, which may be used to capture images of
passing
vehicles, pedestrians, and/or bicycles. The building 125 may have an
associated
database that stores event information (e.g., time of event, duration of
event, location
of event, number of people for the event, etc.) that may affect traffic
patterns. For
example, if the building 125 is a school, one event may be school letting out
at 3:45
PM, which means more children may be crossing streets near the school. If the
building
125 is a sports venue, one event may be the beginning of the sports event at
7:05 PM
or the end of the sports event at 11:10 PM. Additionally or alternatively, the
building
125 may use one or more of its sensors to detect an event. For example, a
school may
use an audio sensor to detect a ringing bell, which may indicate that the
school just let
the students out. As another example, the sports venue may include a camera or
a
pressure sensor on the ground which may detect the number or density of
pedestrians.
A large number or density of pedestrians may indicate that the sports event
just began
or just ended. As will be described in further detail below, the building 125
and/or its
associated database may send sensor or event information to the vehicle and
infrastructure control server 150, and the server 150 may use this information
to adjust
traffic patterns, such as rerouting traffic away from the vicinity of the
building 125,
adjusting the frequency of red lights (e.g., more frequent red lights to give
pedestrians
more opportunities to cross), lowering the speed limit, and the like.
[55] The system 100 may comprise one or more event data sources 145. The event
data
source 145 may store event information for a building 125, as described above.
The
event data source 145 may generally store event information from one or more
calendars (e.g., electronic calendars), such as the event's start time, end
time, duration,
location (e.g., at or near building 125, an intersection, another segment of
road, etc.),
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type (e.g., sports event, school letting out, or another event resulting in a
high number
of pedestrians on or near streets), the expected number of people for the
event (e.g., the
number of pedestrians, such as the number of tickets sold for a sports event,
which may
account for the number of expected no-shows, the number of students enrolled
at a
school etc.), or any other information that may impact traffic. The event data
source
145 may also generate and/or store information for unplanned or other ad hoc
events.
For example, the event data source 145 may generate or store data for a car
crash that
occurred at an intersection or other segment of road, which may have been
detected
using one or more of the sensors 118, 119, 132, or 122 described above. The
event data
source 145 may generate or store data indicating a large number of pedestrians
at, for
example, an intersection. The large number of pedestrians may be detected
using, for
example, signals from the pedestrian's mobile devices 130, traffic cameras
120C at the
intersection, audio sensors at the intersection, or any other sensors
described herein.
The event data source 145 may generate or store other types of events, such as
an
AMBER alert or other wireless emergency alert information (e.g., information
describing the child, the last known location, the time, etc.).
[56] The system 100 may comprise one or more weather data sources 140. Each
weather
data source 140 may comprise one or more database storing weather data, time
data,
location data, etc. The weather data may indicate, for example, whether a
particular
location is snowy (e.g., a blizzard), icy, or rainy (e.g., a torrential
downpour). The
weather data may also indicate sunrise or sunset times at each location, which
may
cause riskier driving conditions if the sun is in the driver's eyes. For
example, sunrises
may be riskier for drivers driving east toward the sun, and sunsets may be
riskier for
drivers driving west. Cloud cover may negate the effect of the sun on drivers,
and
therefore the weather data may indicate the amount of cloud cover at the
location (e.g.,
cloudy, partly cloudy, etc.) Data from the weather data sources 140 may be
accessed
via, for example, open application program interfaces (APIs), databases,
software
development kits (SDKs), V2V communication, and/or mobile device to mobile
device
communication.
[57] The system 100 may comprise one or more map data sources 170. The map
data
sources 170 may generate and/or store one or more street maps that may be used
to map
out navigations, traffic, etc., including third party maps and/or other third
party map
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service provider. The map data source 170 may also generate and/or store map
information for autonomous vehicles, which may be more detailed than maps used
by
non-autonomous vehicles. As will be described in further detail below, map
data from
the map data sources 170 may be used in conjunction with data from one or more
of
the other devices in the system 100 to control traffic flow or for vehicle
navigation.
[58] The system 100 may comprise one or more historical driver or vehicle data
source(s)
175. The data source 175 may generate and/or store data related to drivers,
such as
each driver's risk score, accident history (including location and/or time of
the
accident(s), and context of accident(s), such as whether the driver was going
straight,
turning left, or turning right), driving record, or any other insurance or
safety
information associated with the driver. The data source 175 may generate
and/or store
data related to vehicles, such as the vehicle's make and model, year, accident
history,
maintenance history, the autonomous features supported by the vehicle, etc.
[59] The system 100 may comprise one or more historical traffic and/or
infrastructure data
source(s) 180. The data source 180 may store data for a particular location,
such as an
intersection. The data may indicate the number of accidents at each
intersection, and
the time of the accident (e.g., exact time, time of day, time duration, etc.)
and context
of the accident (e.g., accident involving a rear end, accident involving a
left turn,
accident involving an emergency vehicle, accident involving pedestrian or
bicycle,
accident where a vehicle ran a red light, accident occurring in a particular
lane of traffic,
etc.). The data may comprise insurance data that may provide information
indicating
the riskiness of driving through or turning at an intersection.
[60] FIG. 2 illustrates a block diagram of a computing device 201 in a vehicle
and
infrastructure control system 200 that may be used according to one or more
illustrative
embodiments of the disclosure. The computing device 201 may have a processor
203
for controlling overall operation of the computing device 201 and its
associated
components, including RAM 205, ROM 207, input/output module 209, and memory
unit 215. The computing device 201, along with one or more additional devices
(e.g.,
terminals 241, 251) may correspond to any of multiple systems or devices, such
as
vehicle and infrastructure control devices or systems, configured as described
herein
for determining the status of a traffic device and vehicle movement,
monitoring or
affecting movement of a vehicle using a traffic device, or determining a
navigation
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route based on the location of a vehicle and generating a recommendation for a
vehicle
maneuver.
[61] Input / Output (I/O) module 209 may include a microphone, keypad, touch
screen,
and/or stylus through which a user of the computing device 201 may provide
input, and
may also include one or more of a speaker for providing audio input/output and
a video
display device for providing textual, audiovisual and/or graphical output.
Software
may be stored within memory unit 215 and/or other storage to provide
instructions to
processor 203 for enabling device 201 to perform various functions. For
example,
memory unit 215 may store software used by the device 201, such as an
operating
system 217, application programs 219, and an associated internal database 221.
The
memory unit 215 includes one or more of volatile and/or non-volatile computer
memory to store computer-executable instructions, data, and/or other
information.
Processor 203 and its associated components may allow the computing device 201
to
execute a series of computer-readable instructions to determine the status of
a traffic
device and vehicle movement, monitor or affect movement of a vehicle using a
traffic
device, or determine a navigation route based on the location of a vehicle and
generate
a recommendation for a vehicle maneuver.
[62] The computing device 201 may operate in a networked environment 200
supporting
connections to one or more remote computers, such as terminals / devices 241
and 251.
The computing device 201, and related terminals / devices 241 and 251, may
include
devices installed in vehicles, mobile devices that travel within vehicles, or
devices
outside of vehicles that are configured to receive and process sensor and
contextual
data. Thus, the computing device 201 and terminals / devices 241 and 251 may
each
include personal computers (e.g., laptop, desktop, or tablet computers),
servers (e.g.,
web servers, database servers), vehicle-based devices (e.g., on-board vehicle
computers, short-range vehicle communication systems, sensors and telematics
devices), or mobile communication devices (e.g., mobile phones, portable
computing
devices, and the like), and may include some or all of the elements described
above
with respect to the computing device 201. The network connections depicted in
FIG.
2 include a local area network (LAN) 225 and a wide area network (WAN) 229,
and a
wireless telecommunications network 233, but may also include other networks.
When
used in a LAN networking environment, the computing device 201 may be
connected
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to the LAN 225 through a network interface or adapter 223. When used in a WAN
networking environment, the device 201 may include a modem 227 or other means
for
establishing communications over the WAN 229, such as network 231 (e.g., the
Internet). When used in a wireless telecommunications network 233, the device
201
may include one or more transceivers, digital signal processors, and
additional circuitry
and software for communicating with wireless computing devices 241 (e.g.,
mobile
phones, short-range vehicle communication systems, vehicle sensing and
telematics
devices) via one or more network devices 235 (e.g., base transceiver stations)
in the
wireless network 233. In some aspects, short-range communication technologies,
such
as Bluetooth0, may be used.
[63] It will be appreciated that the network connections shown are
illustrative and other
means of establishing a communications link between the computers may be used.
The
existence of any of various network protocols such as TCP/IP, Ethernet , FTP,
HTTP
and the like, and of various wireless communication technologies such as GSM,
CDMA, Wi-FiO, and WiMAXO, is presumed, and the various computing devices and
vehicle and infrastructure control system components described herein may be
configured to communicate using any of these network protocols or
technologies.
[64] Additionally, one or more application programs 219 used by the computing
device 201
may include computer executable instructions (e.g., vehicle and infrastructure
control
algorithms, and the like) for determining the status of a traffic device and
vehicle
movement, monitoring or affecting movement of a vehicle using a traffic
device, or
determining a navigation route based on the location of a vehicle and
generating a
recommendation for a vehicle maneuver, and performing other related functions
as
described herein.
[65] The vehicle and infrastructure control server 150, which may comprise the
system 200,
may receive data (e.g., sensor data) from one or more of the sensors or other
data
sources described above and analyze the data to determine the condition at one
or more
geographical locations (e.g., intersections, other road segments, near
buildings, etc.).
The server 150 may use the received and analyzed data to take one or more
actions
(and/or send instructions to one or more other devices) to improve pedestrian
and
vehicle safety, improve traffic flow, and the like. Exemplary actions taken
(or
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transmitted) by the vehicle and infrastructure control server 150 (or any
computing
device receiving data) will now be described.
[66] A computing device, such as the vehicle and infrastructure control server
150 and/or a
traffic device 120, may modify traffic signals in response to receiving sensor
or other
data. In some aspects, the sensor data may indicate that an accident occurred
at and/or
within a threshold distance of the intersection. For example, a microphone may
have
captured sounds indicative of an accident involving one or more vehicles,
bicycles,
pedestrians, etc. A camera may have captured images indicative of an accident.
Data
from vehicle sensors 119 and/or mobile device sensors 118 (e.g., impact
sensors, airbag
deployment sensor, GPS or other location sensors, etc.) may be used to
determine that
an accident occurred at the intersection. Any of the sensors described herein
may
capture data indicative of an accident or other event that affects traffic
flow through an
intersection. The computing device may determine the degree of damage cause by
the
accidents, which may be determined based on the number of vehicles involved in
the
accident, the speed of the vehicles involved in the accident, the types of
vehicles
involved in the accident (e.g., sedan, SUV, motorcycle, etc.). Data may
indicate other
events as described herein, such as traffic congestion, events causing large
crowds, etc.
[67] The computing device may send an instruction to adjust the timing of a
traffic light,
such as to turn the light red, yellow, or green and/or to extend the color of
a light (e.g.,
extend the green light). The traffic light may flash its light to indicate a
hazard at or
near the intersection. A traffic device 120 may initiate an audible warning
siren and/or
an audio statement. For example, stoplights or other signals may be used to
prevent the
progress of catastrophic events, such as additional accidents. In some
aspects, the
traffic light may change on the degree of damage of the accidents (e.g.,
number, speed,
type, etc. of vehicles). Whether (and how) to adjust the lights may
additionally or
alternatively be based on the degree of importance of the traffic passing
through the
intersection. For example, the degree of importance may be high for
intersections with
high traffic volumes and lower for intersections with low traffic volumes.
Some
intersections may be tagged as highly important (or not). The degree of
importance
may also be determined based on the number of individuals interrupted (or
potentially
interrupted) by an accident or traffic congestion at the intersection.
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[68] The computing device may instruct the traffic light to switch to a
different color or
status in order to prevent an accident. For example, a sensor measuring
westbound or
eastbound traffic at an intersection may capture data that indicates that a
vehicle is
likely to run a red light. For example, the speed of the eastbound or the
westbound
vehicle may exceed a threshold speed such that the vehicle is likely to run
the red light
with or without braking. As another example, a mobile device sensor may
determine
that the driver is distracted if the driver is using the mobile device, using
certain
applications on the mobile device, etc. In response to the driver's speed
and/or a
determination that the driver is distracted, the computing device may instruct
the traffic
light facing the northbound and/or southbound lanes to turn red and/or keep it
red a
little longer to prevent vehicles from entering the intersection and
consequently
preventing a potential accident involving a vehicle running a red light.
[69] The traffic device may display, via its display device, a message or
written statement
to drivers passing through or by the intersection (e.g., warning drivers of an
accident,
traffic congestion, or any other events that may affect traffic flow). In some
aspects,
the display device might be used for other purposes, such as advertising. For
example,
the display device may comprise a billboard, which may be configured to
display one
or more advertisements. The advertisement displayed on the billboard may
change in
response to sensor or other data. For example, the advertisement may be
adjusted based
on the type of vehicles (e.g., make and/or model) passing through the
intersection or
other segment of road or the type of mobile devices (e.g., ANDROID or i0S0)
in
those vehicles.
[70] A computing device, such as the vehicle 110, the mobile computing device
116, the
traffic device 120, and/or the vehicle and infrastructure control server 150,
may adjust
one or more speed limits or speeds for vehicles in response to receiving
sensor or other
data. The computing device may adjust the speed limit at or near an
intersection or any
other segment of road based on one or more variable risk factors. For example,
if a risk
score of the intersection increases, the computing device may slow down the
speed limit
at or near the intersection (or approaching the intersection). The speed limit
may be
adjusted for certain lanes of the segment of road. For example, if there is a
gas station
or other venue on the right side of a road, the computing device may determine
congestion (or the potential for congestion) in the right lane caused by more
vehicles
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turning right. In response, the computing device may lower the speed limit for
the right
lane for one or more segments of road approaching the gas station or other
venue.
Additionally or alternatively, the computing device may be used to optimize
commerce
opportunities, such as by detecting where commerce is about to occur (e.g.,
lots of
people going to a certain gas station). The computing device may instruct a
display
device to, for example, display advertisements at or before that location.
[71] As another example, the computing device may determine that an emergency
vehicle
(e.g., ambulance, fire truck, etc.) is approaching an intersection or other
segment of
road. The computing device may increase the speed limit for the left lane for
one or
more segments of road such that vehicles may speed up to get out of the way of
the
approaching emergency vehicle. Alternatively, the computing device may
decrease the
speed limit for the left lane in order to incentivize vehicles to move to the
right lanes
such that the emergency vehicle can pass. As described above, one or more
audio or
video messages may be used to warn drivers of approaching emergency vehicles.
[72] The speed limit may also be adjusted for one or more driver or vehicle.
That is, the
speed limit can be dynamic for individual vehicles or drivers. Adjusting the
speed limit
vehicle-by-vehicle may be based on one or more of the following factors:
detecting low
tire pressure, detecting tire burst, detecting the driver's health condition
(e.g., fatigue,
or other health condition), detecting an accident ahead of the vehicle in a
particular
lane, detecting a vehicle ahead turning on its hazard lights, detecting a
maintenance
issue (e.g., detected by onboard vehicle diagnostics), etc.
[73] In some aspects, the speed limit for roads or road segments may be
dynamically
changed based on one or more factors, such as the time of day, traffic
congestion on the
road or road segment, the risk score for the segment of road, planned or ad
hoc events,
among other factors. FIG. 4 is a flow diagram illustrating an example method
of
monitoring or affecting movement of a vehicle using a traffic device according
to one
or more aspects of the disclosure.
[74] The computing device may determine planned events based on, for example,
calendar
information. In step 405, an event data source may transmit, e.g., to a
vehicle and
infrastructure computing device, information indicative of an event affecting
a portion
of road. In step 410, the computing device may determine one or more traffic
devices
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associated with the portion of road and configured to control traffic for the
portion of
road, such as traffic lights, speed limit displays, and the like. In step 415,
the computing
device may send, to the one or more traffic devices associated with the
portion of road,
instructions to change one or more characteristics of the one or more traffic
devices.
The sending may be based on the information indicative of the event affecting
the
portion of road. Several examples of changing the characteristics will now be
provided.
[75] The speed limit may be adjusted to cause drivers to drive at the safest
speed for that
road segment and/or time of day. If a safer possible speed exceeds the speed
limit, the
speed limit may be increased to match or exceed the safer possible speed. The
speed
limit may be decreased during rush hour, during heavy traffic congestion, if
the risk
score (e.g., risk score for a road segment, such as an intersection) is high,
and/or during
events that may cause traffic congestion or other dangers. The timing, such as
frequency, of red lights at a traffic light may additionally be increased in
conjunction
with (or independently from) the speed limit being decreased, such as based on
calendar
information indicating one or more events that may affect certain segments of
road.
The number of pedestrians expected as a result of the event may be compared to
a
threshold number of pedestrians. The speed limit may be increased during non-
peak
hours, during low traffic congestion, if the risk score is low, and/or if no
special events
are planned.
[76] The speed and/or speed limit of a vehicle may be adjusted in order to
prevent an
accident, such as to cause the vehicle to miss another vehicle at an
intersection. For
example, a sensor measuring westbound or eastbound traffic at an intersection
may
capture data that indicates that a vehicle is likely to run a red light. The
speed of the
eastbound or the westbound vehicle may exceed a threshold speed such that the
vehicle
is likely to run the red light with or without braking. As another example, a
mobile
device sensor may determine that the driver is distracted if the driver is
using the mobile
device, using certain applications on the mobile device, etc. In response to
the driver's
speed and/or a determination that the driver is distracted, the computing
device may
increase and/or decrease the speed limit for the northbound or southbound
vehicle to
prevent it from colliding with the vehicle running the red light at the
intersection.
[77] The computing device may indicate the speed limit to drivers in various
ways. For
example, electronic displays on the road may be used to indicate the speed
limit, and
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the computing device may send instructions to one or more of the electronic
displays
to adjust the speed limit, such as from 55 MPH to 65 MPH. In some aspects,
each lane
of the road or road segment may have a digital display so that the speed limit
for each
lane may be adjusted individually. The computing device may send instructions
to
those digital displays in order to change the speed limit for one or more
lanes. Speed
limits may additionally or alternatively be displayed within vehicles. For
example, a
display device in the vehicle may display the speed limit for the road or the
speed limit
for that driver. The display of a mobile device in the vehicle may also be
used to display
the speed limit, such as if the driver is using a navigation application of
the mobile
device. The display of the vehicle and/or the mobile device may display the
speed limit
for the road, the speed limit for a particular lane, and/or the speed limit
for that particular
vehicle.
[78] In some aspects, the speed of an autonomous vehicle may be adjusted
directly (e.g.,
instead of adjusting the speed limit). In step 420, the computing device may
determine
whether any autonomous vehicles are at or near the affected portion of road.
If so (step
420: Y), the computing device, in step 425, may send, to the autonomous
vehicle(s),
instructions to take one or more actions in response to the event affecting
the portion of
road. Each autonomous vehicle may be instructed to apply brakes, to slow down,
or to
speed up. For example, the computing device may send an instruction to the
autonomous vehicle to adjust its speed, such as to match a safer speed and/or
to match
an adjusted speed limit. In some aspects, autonomous vehicles may be adjusted
to
match the conditions of the road. The speed limit for autonomous vehicles may
be
different from the speed limit for non-autonomous vehicles. For example, the
speed
limit may be 55 MPH for vehicles in an autonomous mode, and faster (e.g., 65
MPH)
for vehicles not in autonomous mode (or vice versa). As previously described,
the
speed limit may be displayed on one or more display devices and/or sent to
autonomous
vehicles directly.
[79] A computing device, such as the vehicle and infrastructure control server
150 and/or a
traffic device 120, may adjust flow through one or more traffic lanes in
response to
receiving sensor or other data. The computing device may open or close certain
lanes
based on road conditions indicated by sensor data. The computing device may
send
commands to display devices 120E on the road to indicate whether a certain
lane is
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open or closed. For example, sensor data may indicate that traffic congestion
has
exceeded a threshold congestion level, and the computing device may open one
or more
additional traffic lanes accordingly. As another example, sensor data may
indicate that
an accident ahead of a particular road segment occurred in one or more lanes.
Based
on this sensor data, the computing device may close the affected traffic lanes
a certain
distance prior to the accident (e.g., 1 mile, 1/4 mile, etc. from accident).
As another
example, the computing device may close certain lanes (e.g., left lanes, left
turn lanes,
shoulder lanes, etc.) to regular traffic to allow other types of vehicles to
pass, such as
emergency vehicles, maintenance trucks, snow plows, etc. In addition to
closing lanes
to regular traffic, the computing device may align a plurality of traffic
lights on the
route of the emergency vehicle (e.g., by turning them green). The computing
device
may detect the presence of these emergency vehicles based on traffic cameras,
microphones configured to listen for sirens, GPS location data for emergency
vehicles,
etc.
[80] A computing device, such as the vehicle and infrastructure control server
150, may
contact (e.g., call, broadcast, or otherwise communicate) a broadcast or
emergency
receiver 185 in response to receiving sensor or other data. For example, if a
sensor
hears or sees a car crash, the computing device may call emergency vehicles to
the
location of the car crash. Sensors inside of vehicles (e.g., vehicle sensors
119 and/or
mobile device sensors 118) may also be used to detect emergency conditions in
the car,
such as a heart attack, a birth, or other medical issues. The computing device
may also
send notification of, for example, an AMBER alert to the broadcast and/or
emergency
receiver 185 for the receiver 185 to initiate proper protocols for these
emergency
situations, such as contacting emergency personnel.
[81] A computing device, such as the vehicle and infrastructure control server
150 and/or
the traffic device 120, may contact (e.g., call, broadcast, or otherwise
communicate)
government authorities or their devices to improve driving conditions in
response to
receiving sensor or other data. For example, sensors on the road (e.g., water
depth
sensors), in the vehicle 110, and/or in the mobile device 116 may sense ice
buildup
(e.g., if vehicles are sliding on the road), excess water buildup (e.g., if
vehicles are
hydroplaning or otherwise slipping), or any other potentially dangerous
conditions.
The computing device may call the appropriate government authorities, which
may
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come to plow and/or lay down salt for the road. If available, the computing
device may
electrify or otherwise heat the road to cause ice or snow to melt.
Environmental
conditions on ramps may be determined in a similar manner.
[82] A computing device, such as the vehicle and infrastructure control server
150, the traffic
device 120, and/or the vehicle 110, may communicate with vehicles, such as
sending
instructions or other data, in response to receiving sensor or other data. For
example,
the computing device and/or intersection infrastructure may broadcast the
status of the
intersection (e.g., the color of the light, an anomaly at the intersection,
such as an
accident, etc.) to nearby vehicles.
[83] As previously described, the computing device may send instructions to
autonomous
vehicles to control the vehicle, such as to increase or decrease the vehicle's
speed. For
example, the computing device may send an instruction to the vehicle to adjust
the level
of autonomy, such as to turn off autonomous mode (e.g., switch to manual
mode), or to
switch to an autonomous safe mode (e.g., a semi-autonomous mode). Similarly,
the
computing device may send an instruction to the autonomous vehicle to take a
specific
action, such as to brake, to slow down, or to speed up. The computing device
may send
the instruction in response to detecting an event at the intersection, such as
unusual
congestion, a traffic accident, an unusual number of pedestrians or bicycles,
etc.
[84] As another example, the computing device may determine that a vehicle
approaching
an intersection and going the opposite direction of an autonomous vehicle is
turning
left. The computing device may make this determination based on sensor data,
such as
data from a traffic camera showing that the vehicle is in a left turn lane
and/or has its
left turn blinkers on, data from a navigation application of the vehicle
guiding the
vehicle to make a left turn at the intersection, the vehicle slowing down at a
certain rate
of speed at the intersection, or any other sensor data. Based on the
determination that
the vehicle going the opposite direction of the autonomous vehicle is turning
left, the
computing device may send one or more instructions to the autonomous vehicle.
For
example, the computing device may instruct the autonomous vehicle to slow down
or
stop to allow the other vehicle to turn left.
[85] The computing device may make similar determinations and send similar
instructions
for vehicles going the same direction as the autonomous vehicle. For example,
the
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computing device may determine that a vehicle traveling in the same direction
as (and
in the same lane as) the autonomous vehicle is expected to turn left or right
at an
intersection. The computing device may instruct the autonomous vehicle in the
same
lane as the vehicle that is about to turn left or right to slow down or stop
in anticipation
of the vehicle in front of the autonomous vehicle slowing down in order to
turn.
[86] Traffic infrastructure may be used to sense the condition of a vehicle,
and to
communicate the condition of the vehicle to the driver and/or vehicle. For
example, a
traffic camera 120C may capture one or more images of a passing vehicle. The
traffic
camera 120C or other computing device may process the images (e.g., in real
time) to
determine a condition of the vehicle. For example, the computing device may
determine, based on the captured image, that the vehicle has low tire
pressure. The
computing device may determine that the vehicle's headlamp is off at
nighttime. In
response to determining the condition of the vehicle that may require action
by the
driver, the computing device may send to the vehicle and/or a mobile device in
the
vehicle an indication of the condition of the vehicle. The vehicle and/or
mobile device
may display or otherwise indicate to the driver the condition of the vehicle,
such as if
the tire pressure is low or the headlamp is off when it should be on. In some
examples,
the computing device may transmit an instruction to the vehicle causing the
headlights
to turn on automatically (e.g., without driver interaction).
[87] FIGS. 3A-B are flow diagrams illustrating example methods of determining
a status of
a traffic device and vehicle movement according to one or more aspects of the
disclosure. The computing device may be used to detect distracted driving,
such as a
distracted driver at an intersection. With reference to FIG. 3A, in step 305,
a camera
(e.g., a traffic camera) or another type of presence sensor at the
intersection may be
used to detect movement of a vehicle after a red light at the intersection
turns green.
For example, the traffic camera may transmit one or more images of the vehicle
captured by the traffic camera. Based on the one or more images of the vehicle
captured
by the traffic camera, the computing device may determine the time that the
vehicle at
the location of the traffic device moved.
[88] Sensors 119 in the vehicle 110 and/or sensors 118 in the mobile
device 116 may also
be used to detect vehicle movement. For example, the mobile device and/or the
vehicle
may have one or more of a position sensor, speed sensor, or acceleration
sensor for
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detecting movement. In step 310, the mobile device and/or vehicle may transmit
to the
computing device data indicative of one or more of a position, speed, or
acceleration of
the vehicle (e.g., based on sensor data). In step 315, the computing device
may
determine, based on the sensor data, whether the vehicle moved. If not, the
computing
device may proceed to step 320. Alternatively, in step 325, the computing
device may
determine the time that the vehicle at the location of the traffic device
moved based on
the sensor data (e.g., data indicative of one or more of the position, speed,
or
acceleration of the vehicle).
[89] In some aspects, a traffic device, which may comprise one or more traffic
signals, may
transmit, via its transceiver and to a vehicle and infrastructure computing
device,
information indicative of a status of the one or more traffic signals (e.g.,
whether the
signal is red, yellow, green, etc.). With reference to Fig. 3B, in step 330,
the computing
device may receive, from the traffic device, the information indicative of the
status of
the one or more traffic signals. In step 335, the computing device may
determine
whether the traffic signal is red, yellow, green, flashing, etc. For example,
the
computing device may determine that the traffic device switched from a red
light to a
green light. In step 340, the computing device may also determine a time that
the status
of the traffic device changes (e.g., one or more traffic signals of the
traffic device
switched from the red light to the green light). In step 345, the computing
device may
determine an amount of time between the time that the one or more traffic
signals of
the traffic device switched from the red light to the green light and a time
that a vehicle
at a location of the traffic device moved.
[90] In step 350, the computing device may determine whether the amount of
time from
when the vehicle moved is within a threshold amount of time. If not (step 350:
N), the
computing device, in step 355 may determine that the driver is distracted. For
example,
the driver may be texting or otherwise using a mobile device at the
intersection and not
react quickly enough to the traffic light turning green. That is, the driver
might be slow
to step on the gas pedal after the light turns green. In some aspects, the
computing
device may compare the driver's reaction time (e.g., 5 seconds) to a threshold
(e.g.,
typical) reaction time (e.g., 1 or 2 seconds). If the driver's reaction time
exceeds the
threshold (e.g., by a certain amount of time), the computing device may
determine that
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the driver is distracted. Otherwise, the computing device in step 360 may
determine
that the driver is not distracted.
[91] The computing device may perform one or more actions based on a
determination that
the driver is distracted (e.g., a reaction time lower than a threshold
reaction time). For
example, the computing device may adjust the driver's risk score and/or charge
the
driver a higher insurance premium if it is determined that the driver is
distracted. In
step 320, the computing device may also send a message to the vehicle 110
and/or
mobile device 116 for display to the driver. For example, the message may
indicate
that the light is green (e.g., that the light switched from red to green) and
for the driver
to go on green. Prior to the light turning green, the computing device may
send a
message to the vehicle or mobile device indicating when light will turn green,
such as
a countdown. The messages may be used to audibly or visually notify the
driver. The
message may be a warning against inattentive driving, and in some cases, may
comprise
a traffic ticket.
[92] FIG. 6 is a flow diagram illustrating an example method of sending
instructions to
and/or controlling a device (e.g., a mobile device) in a vehicle based on the
status of a
traffic device according to one or more aspects of the disclosure. An
application or
service may be installed on a mobile device, and the application or service
may prevent
the mobile device from being used in certain situations. If the vehicle is at
the location
of a traffic light, and the traffic light is red, the computing device may
send an
instruction to the mobile device of the driver (e.g., the application or
service installed
on the mobile device) to allow driver interaction with the mobile device while
the one
or more traffic signals of the traffic device is red. For example, in step
605, the
computing device may determine the status of a traffic light (e.g., red,
yellow, green,
etc.). In step 610, the computing device may determine whether the traffic
light is red.
If the traffic light is red (step 610: Y), the computing device, in step 615,
may enable
use of the mobile device while the light is red. For example, the computing
device may
send an instruction to the mobile device of the driver (e.g., the application
or service
installed on the mobile device), and the instruction may cause the application
or service
on the mobile device to turn off one or more prevention features that prevent
the mobile
device from being used by the driver (or otherwise enable use of the mobile
device and
one or more applications thereof). Once the light turns green (or at a
predetermined
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time before it turns green, such as 10 seconds), the computing device may send
an
instruction to the mobile device that prevents the user from texting or
otherwise
interacting with the mobile device. For example, in step 620, the computing
device
may determine whether the traffic light is green. If so (step 620: Y), the
computing
device, in step 625, may send an instruction (e.g., to the application or
service installed
on the mobile device) to prevent the driver from using one or more
applications of the
mobile device, such as a messaging (e.g., texting) application, or otherwise
prevent the
driver from using the mobile device or application on the mobile device. The
instruction may cause the application or service to disable one or more other
applications or services on the mobile device. Otherwise (step 620: N), the
computing
device may return to step 610 to wait for the light to turn green.
[93] In some aspects, the computing device may provide the driver (e.g., via
the mobile
device, vehicle, or other computing device) with information indicative of how
the
driver compares to other drivers. For example, the driver may be provided with
information indicative of the driver's speed relative to other drivers' speeds
(e.g., if the
driver is in the top 1% of speed). The computing device may provide additional
information, such as the driver's reaction time to lights, the driver's risk
score, etc.
[94] Aspects described herein may be used for automatic donations. For
example,
volunteers are often at intersections collecting donations for their cause.
Rather than
having volunteers walk around collecting money for charity at the intersection
(which
may be unsafe), the user may automatically make a donation via the user's
mobile
device and/or a button in the vehicle. In some aspects, the driver might only
be
permitted to make a donation if the light is red or the vehicle is otherwise
stopped at
the intersection. As a result, volunteers, such as firefighters, collecting
donations at
intersections or other portions of road may be safer than if these volunteers
physically
collected the donations.
[95] FIGS. 7A-B are flow diagrams illustrating example methods of sending
instructions to
and/or controlling a traffic device and/or mobile device to control the flow
of
pedestrians, bicyclists, etc. through an intersection according to one or more
aspects of
the disclosure. A computing device, such as the vehicle and infrastructure
control
server 150, a mobile computing device 130, and/or the traffic device 120, may
communicate with or modify the flow of pedestrians or bicyclists through a
portion of
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road, such as an intersection. In some aspects, the computing device may
disable one
or more functionalities of a pedestrian's mobile device based on the
pedestrian's
distance from or proximity to an intersection. For example, and with reference
to FIG.
7A, the computing device, in step 705, may determine a pedestrian's location
based on
a sensor of the mobile device 130 (e.g., GPS or other location sensor), a
sensor at the
intersection (e.g., a camera), or any other sensors. In step 710, the
computing device
may determine that the pedestrian is approaching the intersection (e.g.,
within a
threshold distance from the intersection, such as 10 feet). In response to
these
determination(s), the computing device, in step 715, may send an instruction
to the
mobile device for the mobile device to turn off, to turn off a screen, and/or
to stop an
application (e.g., to prevent the pedestrian from texting). In step 720, the
computing
device may also send an instruction to the mobile device for the device to
display a
message requesting the pedestrian to stop using the mobile device has the
pedestrian
approaches the intersection. As a result, the pedestrian might not be able to
(or be less
inclined to) use his or her mobile device in certain ways while crossing a
street or
intersection.
[96] In some aspects (and with reference to FIG. 7B), the computing device may
use
infrastructure, such as a pedestrian barrier, at an intersection or other
portion of road to
prevent pedestrians from crossing. Based on sensor data, the computing device,
in step
730, may detect an unsafe condition at the intersection, such as a vehicle
about to run a
red light, a traffic accident, the presence of an emergency vehicle
approaching the
intersection, or any other unusual condition or event. In response to
determining that
the intersection is not safe for pedestrians, the computing device, in step
735, may send
an instruction to activate (e.g., raise or lower) a physical barrier (e.g.,
the barrier 120D)
to prevent pedestrians from entering the intersection or otherwise crossing
the road. In
some aspects, the barrier may be similar to a train crossing or subway
crossing barrier,
or may be any type of physical barrier that blocks pedestrians from entering
the road.
In step 740, the computing device may additionally or alternatively send an
instruction
to a speaker at the intersection to generate a high-pitched sound that when
initiated,
causes pedestrians to freeze, collapse, or otherwise stop walking at the
intersection.
The computing device may also send an instruction to a display at the
intersection to
instruct pedestrians not to cross, such as a do not walk signal.
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[97] Instead of (or in addition to) controlling infrastructure on the road,
the computing
device may send commands to a pedestrian's mobile device to prevent the
pedestrian
from crossing the road. For example, the computing device may send an
instruction for
the mobile device to emanate a high-pitched sound that causes the pedestrian
to stop.
The computing device may similarly send an instruction to the mobile device to
vibrate,
playback an audio message, and/or display a visual message to instruct the
pedestrian
not to cross the intersection (or to otherwise notify the pedestrian of an
event affecting
a portion of road). An audio alert may be presented to the pedestrian through
headphones plugged in to the mobile device and/or through the mobile device's
speakers. The computing device may also send an instruction to the headphones
to turn
off active noise cancellation when the pedestrian approaches intersection.
[98] A computing device, such as the vehicle and infrastructure control server
150, may
collect data before, during, and after an accident to determine fault in
response to
receiving sensor or other data. The data may be stored in one or more
databases, which
may be used to determine fault and to issue claims. For example, the data may
be
incorporated in the historical driver and vehicle data source 175. As
previously
explained, traffic cameras may be used to detect accidents, and the captured
images
may be used to assist in determining claims and/or fault. Location data (e.g.,
GPS data),
speed data, acceleration data, weather data, images data, etc. may be used to
determine
accidents and/or fault. This data may be combined with data indicating the
status and/or
risk scores of intersections or other segments of road, such as whether the
light was red,
the speed limit of the segment of road, etc., to determine fault.
[99] A computing device, such as the vehicle and infrastructure control server
150, may
adjust navigation score(s) (e.g., risk score(s)) for each intersection (or
other portion of
a road) in response to receiving sensor or other data. Each intersection may
have an
intersection risk score, and the computing device may determine the
intersection risk
score based on one or more factors, such as the complexity of the intersection
(e.g., the
number streets passing through the intersection), the number of accidents
historically
occurring at the intersection, weather, traffic congestion, and other dynamic
factors. If
an accident occurs at the intersection, the computing device may increase the
risk score
for the intersection. An intersection path risk map may be generated based on
the risk
scores for each intersection on the map.
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[100] A computing device, such as the vehicle and infrastructure control
server 150, may
generate one or more recommended driving routes (e.g., navigation routes) in
response
to receiving sensor or other data. For example, the computing device may
generate
navigation routes based on intersection risk scores, risk scores for one or
more other
segments of road, and/or insurance cost data. The navigation route may be
provided to
the driver on a display of the driver's vehicle 110, on the display of the
mobile device
116, etc. If multiple routes are available, the driver may be able to compare
each route
and select a route to take. One or more of the routes may be designated a
preferred
route, such as if the route has the lowest cumulative risk score.
[101] FIG. 5 is a flow diagram illustrating an example method of determining a
navigation
route based on the location of a vehicle and generating a recommendation for a
vehicle
maneuver according to one or more aspects of the disclosure. In step 505, the
computing device may receive sensor data from, for example, a location sensor
of a
mobile device or a vehicle. In step 510, the computing device may determine
the
location of the vehicle based on the sensor data. As previously described (and
as
illustrated in step 515), the computing device may determine a navigation
route for
navigating the vehicle from the location to a destination.
[102] The navigation route may comprise a plurality of intersections. In step
520, the
computing device may determine a plurality of potential maneuvers at one or
more of
the intersections. In step 525, the computing device may analyze each maneuver
through an intersection, and generate a navigation score for each of those
maneuvers.
The navigation scores may be based on one or more factors described herein.
For
example, the navigation score (e.g., a cost, such as an insurance cost) of
turning left at
an intersection may be X, whereas the navigation score (e.g., a cost) of
making three
right turns to achieve the same goal may be Y. In some aspects, X may be lower
than
Y (e.g., the single left turn is cheaper, safer, and/or faster), and in other
aspects, Y may
be lower than X (e.g., the three right turns is cheaper, safer, and/or
faster). That is, the
computing device may determine whether to recommend a left turn or three right
turns
to the driver for one or more intersections, based on the risk score of the
intersection.
Going straight through the intersection may also have a navigation score
assigned to it.
Another type of maneuver may be a U turn at the intersection. In step 530, the
navigation scores may be analyzed by the computing device and used to provide
one or
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more proposed maneuvers (and consequently routes) to the driver. For example,
the
computing device may wirelessly transmit a selected maneuver to a navigation
application running on the mobile device or the vehicle's system. In some
aspects, the
navigation scores may be used by a routing application to generate a driving
route.
[103] Driver preferences may be included in determining risk scores and/or
recommended
navigation routes. A driver may prefer particular types of intersections or
maneuvers.
For example, the driver might not desire to perform certain maneuvers, such as
left
turns or U turns. Drivers may also prefer to drive below certain speeds, such
as 40
MPH. Preferences may be based on how long the driver has been driving, such
that
more complex maneuvers may be less desired than simpler maneuvers. The driver
may
provide these preferences to the computing device (e.g., by inputting
preferences into
the mobile device 116, vehicle 110, or other computing device), and the
computing
device may factor in these preferences to determine whether to recommend a
particular
path or maneuver. For example, the computing device might not recommend a
navigation path that includes a highway if the driver desires to stay below 40
MPH, or
may recommend three right turns instead of a left turn if the driver does not
desire to
make a left turn.
[104] The computing device may also determine the navigation score and/or risk
based on
individual lanes on a segment of road, such as a highway. That is, each lane
may have
a different risk. For example, the right lane may be riskier than the middle
lane or left
lane on a city street, or the left lane may be riskier than the right lane on
a freeway. The
computing device may determine the navigation score for a particular route
based on
which lanes the driver is expected or recommended to travel on for a
particular portion
of the route.
[105] Some intersections or other segments of road might not permit certain
types of vehicles,
such as autonomous vehicles. If the computing device determines that the
vehicle to
be navigated is an autonomous vehicle, the computing device may avoid these
intersections that do not permit autonomous vehicles. That is, the computing
device
may reroute the autonomous vehicle through a different intersection. In some
aspects,
these intersections may permit autonomous vehicles, but driving autonomous
vehicles
through these intersections may be dangerous. One or more of the factors used
to
determine scores for maneuvers at intersections may include a level of
autonomy of the
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vehicle (e.g., manual, semi-autonomous, fully autonomous, the number of
autonomous
features of the vehicle, etc.). Accordingly, the computing device may
determine the
navigation score for each potential maneuver based on the level of autonomy of
the
vehicle. The computing device may increase the risk score accordingly to
disincentivize a route that includes one or more of these intersections.
[106] Based on recommended routes, the computing device may send instructions
to the
vehicle to switch between autonomous mode and non-autonomous mode. For
example,
if the vehicle will be traveling through an intersection that prohibits
autonomous
vehicles or that is dangerous for autonomous vehicles, the computing device
may
instruct the vehicle to switch to non-autonomous mode. The computing device
may
activate or deactivate (e.g., turn on or off) individual autonomous vehicle
features. For
example, the computing device may receive, from a vehicle or mobile device,
data
indicating that the vehicle is approaching an intersection. In response to
receiving the
data indicating that the vehicle is approaching the first intersection, the
computing
device may send, to the vehicle, an instruction to deactivate one or more of
its
autonomous features. Moreover, the type of maneuver through the intersection
may be
determined based on whether the vehicle is autonomous or not. For example, the
computing device may instruct non-autonomous vehicles to make a left turn
through a
certain intersection, and may instruct autonomous vehicles to make right turns
and/or
to go straight through the intersection. The computing device may also send
the
selected maneuver to the autonomous vehicle. One maneuver may be recommended
if
the vehicle is autonomous, while another maneuver may be recommended if the
vehicle
is not autonomous. In some aspects, vehicles and/or mobile devices with
vehicles may
have the ability to detect the type of intersection (e.g., smart intersection
or standard
intersection), and may send data indicating the type of intersection to the
vehicle and
infrastructure control server 150 and/or another central repository.
[107] A computing device, such as the vehicle and infrastructure control
server 150, may
adjust a characteristic of an insurance policy based on the driver's route,
including
which intersections the driver passes through and which turns the driver makes
at the
intersection. The computing device may adjust a driver's insurance premium if
the
driver goes through a risky intersection, which may be based on the risk score
for the
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intersection. For example, the driver might not have followed the route
recommended
by the computing device.
[108] As previously explained, the computing device may determine one or more
risk score
for the intersection. Intersection route risk scores may be based on one or
more static
factors and/or one or more dynamic factors. Static factors may include, for
example,
past accident information and the like. Dynamic factors may include, for
example,
information regarding the risk level of other vehicles on the road, the time
of day, the
current weather, etc. If there is an accident at an intersection, the risk
score of the
intersection may increase. In some instances, the risk score may increase
significantly
over a short period of time, such as if the accident at the intersection has
not cleared.
Once the accident has been cleared, the risk score for the intersection may
return to
normal levels (or slightly higher levels to account for the new accident).
Intersections
may be provided with a plurality of different risk scores, depending on a
car's direction
of travel through the intersection. For example, different risk scores may be
assigned
to northbound travel, southbound travel, eastbound travel, and westbound
travel
through the intersection.
[109] The characteristic of the insurance policy may also be adjusted based on
whether the
driver is a distracted driver, as previously described. The insurance premium
may be
increased if the driver is a distracted driver, but decreased if the driver is
an attentive
driver.
[110] An exemplary method described herein may comprise determining, based on
sensor
data received from a location sensor of a mobile device or a vehicle, a
location of the
vehicle. The method may comprise determining, by a computing device, a
navigation
route for navigating the vehicle from the location to a destination, wherein
the
navigation route comprises a plurality of intersections. The method may
comprise
determining, by the computing device, a plurality of potential maneuvers at a
first
intersection of the plurality of intersections. The method may comprise
determining,
by the computing device and based on one or more factors, a navigation score
for each
of the plurality of potential maneuvers at the first intersection. The method
may
comprise, based on the navigation score for each of the plurality of potential
maneuvers,
selecting a maneuver from the plurality of potential maneuvers to recommend
for the
vehicle.
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1111] In some aspects, the computing device may be at a location remote from
the location
of the vehicle. The method may further comprising wireless transmitting, by
the
computing device, the selected maneuver to a navigation application associated
with
one or more of the mobile device or the vehicle.
[112] In some aspects, the one or more factors may comprise a level of
autonomy of the
vehicle, and determining the navigation score for each of the plurality of
potential
maneuvers may comprise determining the navigation score for each of the
plurality of
potential maneuvers based on the level of autonomy of the vehicle.
[113] In some aspects, the vehicle may comprise an autonomous vehicle, and the
method may
further comprise sending the selected maneuver to the autonomous vehicle.
[114] In some aspects, the vehicle may have a plurality of autonomous features
activated, and
the method may further comprise receiving, by the computing device and from
one or
more of the vehicle or mobile device, data indicating that the vehicle is
approaching the
first intersection. The method may comprise, in response to receiving the data
the
indicating that the vehicle is approaching the first intersection, sending, to
the vehicle,
an instruction to deactivate one or more of the plurality of autonomous
features.
[115] In some aspects, the one or more factors may comprise whether the
vehicle is
autonomous. The method may further comprise determining, by the computing
device,
whether the vehicle is autonomous. The selecting the maneuver may comprise
selecting
a first maneuver to recommend if the vehicle is autonomous and selecting a
second
maneuver to recommend if the vehicle is not autonomous.
[116] In some aspects, the plurality of potential maneuvers at the first
intersection may
comprise at least two of a right turn at the first intersection, a left turn
at the first
intersection, a U turn at the first intersection, and proceeding straight
through the first
intersection.
[117] In some aspects, the method may further comprise determining, by the
computing
device, an intersection score for each of the plurality of intersections based
on one or
more of a complexity of the intersection, a number of accidents at the
intersection,
weather, or traffic congestion.
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[118] An exemplary apparatus described herein may comprise a processor, and
memory
storing computer-executable instructions that, when executed by the processor,
may
cause the apparatus to: determine, based on sensor data received from a
location sensor
of a mobile device or a vehicle, a location of the vehicle; determine a
navigation route
for navigating the vehicle from the location to a destination, wherein the
navigation
route comprises a plurality of intersections; determine a plurality of
potential
maneuvers at a first intersection of the plurality of intersections;
determine, based on
one or more factors, a navigation score for each of the plurality of potential
maneuvers
at the first intersection; and based on the navigation score for each of the
plurality of
potential maneuvers, select a maneuver from the plurality of potential
maneuvers to
recommend for the vehicle.
[119] In some aspects, the apparatus may be at a location remote from the
location of the
vehicle, and the memory may store computer-executable instructions that, when
executed by the processor, cause the apparatus to wireless transmit the
selected
maneuver to a navigation application associated with one or more of the mobile
device
or the vehicle.
[120] In some aspects, one or more factors may comprise a level of autonomy of
the vehicle,
and determining the navigation score for each of the plurality of potential
maneuvers
may comprise determining the navigation score for each of the plurality of
potential
maneuvers based on the level of autonomy of the vehicle.
[121] In some aspects, the vehicle may comprise an autonomous vehicle, and the
memory
may store computer-executable instructions that, when executed by the
processor, cause
the apparatus to send the selected maneuver to the autonomous vehicle.
[122] In some aspects, the vehicle may have a plurality of autonomous features
activated, and
the memory may store computer-executable instructions that, when executed by
the
processor, cause the apparatus to receive, from one or more of the vehicle or
mobile
device, data indicating that the vehicle is approaching the first
intersection; and in
response to receiving the data the indicating that the vehicle is approaching
the first
intersection, send, to the vehicle, an instruction to deactivate one or more
of the plurality
of autonomous features.
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[123] In some aspects, the one or more factors may comprise whether the
vehicle is
autonomous, and the memory may store computer-executable instructions that,
when
executed by the processor, cause the apparatus to determine whether the
vehicle is
autonomous. Selecting the maneuver may comprise selecting a first maneuver to
recommend if the vehicle is autonomous and selecting a second maneuver to
recommend if the vehicle is not autonomous.
[124] In some aspects, the plurality of potential maneuvers at the first
intersection comprises
at least two of a right turn at the first intersection, a left turn at the
first intersection, a
U turn at the first intersection, and proceeding straight through the first
intersection.
[125] In some aspects, the memory may store computer-executable instructions
that, when
executed by the processor, cause the apparatus to determine an intersection
score for
each of the plurality of intersections based on one or more of a complexity of
the
intersection, a number of accidents at the intersection, weather, or traffic
congestion.
[126] An exemplary non-transitory computer readable medium described herein
may store
instructions that, when read by a computing device, cause the computing device
to:
determine, based on sensor data received from a location sensor of a mobile
device or
a vehicle, a location of the vehicle; determine a navigation route for
navigating the
vehicle from the location to a destination, wherein the navigation route
comprises a
plurality of intersections; determine a plurality of potential maneuvers at a
first
intersection of the plurality of intersections; determine, based on one or
more factors, a
navigation score for each of the plurality of potential maneuvers at the first
intersection;
and based on the navigation score for each of the plurality of potential
maneuvers, select
a maneuver from the plurality of potential maneuvers to recommend for the
vehicle.
[127] In some aspects, the computing device may be at a location remote from
the location
of the vehicle, and the non-transitory computer readable medium may store
instructions
that, when read by the computing device, cause the computing device to
wireless
transmit the selected maneuver to a navigation application associated with one
or more
of the mobile device or the vehicle.
[128] In some aspects, the one or more factors may comprise a level of
autonomy of the
vehicle, and determining the navigation score for each of the plurality of
potential
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maneuvers may comprise determining the navigation score for each of the
plurality of
potential maneuvers based on the level of autonomy of the vehicle.
[129] In some aspects, the vehicle may comprise an autonomous vehicle, and the
non-
transitory computer readable medium may store instructions that, when read by
the
computing device, cause the computing device to send the selected maneuver to
the
autonomous vehicle.
[130] An exemplary system described herein may comprise a traffic device
comprising a
traffic device computer, one or more traffic signals, a transceiver, and first
memory
storing computer-executable instructions that, when executed by the traffic
device
computer, cause the traffic device to transmit, via the transceiver and to a
vehicle and
infrastructure computing device, information indicative of a status of the one
or more
traffic signals. The vehicle and infrastructure computing device may comprise
a vehicle
and infrastructure control computer, and second memory storing computer-
executable
instructions that, when executed by the vehicle and infrastructure control
computer,
cause the vehicle and infrastructure computing device to receive, from the
traffic
device, the information indicative of the status of the one or more traffic
signals;
determine that the information indicative of the status of the one or more
traffic signals
indicates that the one or more traffic signals of the traffic device switched
from a red
light to a green light and a time that the one or more traffic signals of the
traffic device
switched from the red light to the green light; in response to determining
that the one
or more traffic signals of the traffic device switched from the red light to
the green light,
determine an amount of time between the time that the one or more traffic
signals of
the traffic device switched from the red light to the green light and a time
that a vehicle
at a location of the traffic device moved; and in response to determining that
the amount
of time exceeds a threshold amount of time, determine that a driver of the
vehicle is
distracted.
[131] In some aspects, the exemplary system described herein may comprise a
traffic camera,
and the second memory may store computer-executable instructions that, when
executed by the vehicle and infrastructure control computer, cause the vehicle
and
infrastructure computing device to receive, from the traffic camera, one or
more images
of the vehicle captured by the traffic camera; and based on the one or more
images of
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the vehicle captured by the traffic camera, determine the time that the
vehicle at the
location of the traffic device moved.
[132] In some aspects, the system may further comprise a mobile device having
one or more
of a position sensor, speed sensor, or acceleration sensor, and the second
memory may
store computer-executable instructions that, when executed by the vehicle and
infrastructure control computer, cause the vehicle and infrastructure
computing device
to receive, from the mobile device or the vehicle, data indicative of one or
more of a
position, speed, or acceleration of the vehicle; and based on the data
indicative of one
or more of the position, speed, or acceleration of the vehicle, determine the
time that
the vehicle at the location of the traffic device moved.
[133] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to determine that the vehicle is at the
location of
the traffic device and that the one or more traffic signals of the traffic
device is not red;
and in response to determining that the vehicle is at the location of the
traffic device
and that the one or more traffic signals of the traffic device is not red,
send an instruction
to one or more mobile device of the driver to prevent driver interaction with
the mobile
device while the one or more traffic signals of the traffic device is not red.
[134] In some aspects, the instruction may be configured to disable one or
more applications
of the mobile device.
[135] In some aspects, the one or more applications may comprise a messaging
application.
[136] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to: determine that the vehicle is at the
location of
the traffic device and that the one or more traffic signals of the traffic
device is red; and
in response to determining that the vehicle is at the location of the traffic
device and
that the one or more traffic signals of the traffic device is red, send an
instruction to one
or more mobile device of the driver to enable use of the mobile device while
the one or
more traffic signals of the traffic device is red.
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[137] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to: determine that the one or more traffic
signals
of the traffic device switched from red to green; and in response to
determining that the
one or more traffic signals of the traffic device switched from red to green,
send an
instruction to the one or more mobile device of the driver to prevent driver
interaction
with the mobile device while the one or more traffic signals of the traffic
device is
green.
[138] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to based on determining that the driver of
the
vehicle is distracted, adjust a risk score for the driver.
[139] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to in response to determining that the one
or more
traffic signals of the traffic device has switched from the red light to the
green light,
send an instruction to one or more mobile device of the driver or to the
vehicle to
audibly or visually notify the driver that the one or more traffic signals is
a green light.
[140] An exemplary method described herein may comprise receiving, at a
vehicle and
infrastructure computing device and from a traffic device comprising one or
more
traffic signals, information indicative of a status of the one or more traffic
signals. The
method may comprise determining that the information indicative of the status
of the
one or more traffic signals indicates that the one or more traffic signals of
the traffic
device switched from a red light to a green light and a time that the one or
more traffic
signals of the traffic device switched from the red light to the green light.
The method
may comprise, in response to determining that the one or more traffic signals
of the
traffic device switched from the red light to the green light, determining an
amount of
time between the time that the one or more traffic signals of the traffic
device switched
from the red light to the green light and a time that a vehicle at a location
of the traffic
device moved. The method may comprise, in response to determining that the
amount
of time exceeds a threshold amount of time, determining that a driver of the
vehicle is
distracted.
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[141] In some aspects, the method may further comprise receiving, from a
traffic camera, one
or more images of the vehicle captured by the traffic camera, and based on the
one or
more images of the vehicle captured by the traffic camera, determining the
time that
the vehicle at the location of the traffic device moved.
[142] In some aspects, the method may comprise receiving, from a mobile device
or the
vehicle, data indicative of one or more of a position, speed, or acceleration
of the
vehicle, and based on the data indicative of one or more of the position,
speed, or
acceleration of the vehicle, determining the time that the vehicle at the
location of the
traffic device moved.
[143] In some aspects, the method may further comprise determining that the
vehicle is at the
location of the traffic device and that the one or more traffic signals of the
traffic device
is not red, and in response to determining that the vehicle is at the location
of the traffic
device and that the one or more traffic signals of the traffic device is not
red, sending
an instruction to one or more mobile device of the driver to prevent driver
interaction
with the mobile device while the one or more traffic signals of the traffic
device is not
red.
[144] In some aspects, the instruction may be configured to disable one or
more applications
of the mobile device.
[145] In some aspects, the one or more applications may comprise a messaging
application.
[146] An exemplary vehicle and infrastructure computing device may comprise a
vehicle and
infrastructure control computer, and memory storing computer-executable
instructions
that, when executed by the vehicle and infrastructure control computer, cause
the
vehicle and infrastructure computing device to receive, from a traffic device
comprising
one or more traffic signals, information indicative of a status of the one or
more traffic
signals; determine that the information indicative of the status of the one or
more traffic
signals indicates that the one or more traffic signals of the traffic device
switched from
a red light to a green light and a time that the one or more traffic signals
of the traffic
device switched from the red light to the green light; in response to
determining that
the one or more traffic signals of the traffic device switched from the red
light to the
green light, determine an amount of time between the time that the one or more
traffic
signals of the traffic device switched from the red light to the green light
and a time that
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a vehicle at a location of the traffic device moved; and in response to
determining that
the amount of time exceeds a threshold amount of time, determine that a driver
of the
vehicle is distracted.
[147] In some aspects, the memory may store computer-executable instructions
that, when
executed by the vehicle and infrastructure control computer, cause the vehicle
and
infrastructure computing device to determine that the vehicle is at the
location of the
traffic device and that the one or more traffic signals of the traffic device
is red; and in
response to determining that the vehicle is at the location of the traffic
device and that
the one or more traffic signals of the traffic device is red, send an
instruction to one or
more mobile device of the driver to enable use of the mobile device while the
one or
more traffic signals of the traffic device is red.
[148] In some aspects, the memory may store computer-executable instructions
that, when
executed by the vehicle and infrastructure control computer, cause the vehicle
and
infrastructure computing device to determine that the one or more traffic
signals of the
traffic device switched from red to green, and in response to determining that
the one
or more traffic signals of the traffic device switched from red to green, send
an
instruction to the one or more mobile device of the driver to prevent driver
interaction
with the mobile device while the one or more traffic signals of the traffic
device is
green.
[149] In some aspects, the memory may store computer-executable instructions
that, when
executed by the vehicle and infrastructure control computer, cause the vehicle
and
infrastructure computing device to, in response to determining that the one or
more
traffic signals of the traffic device has switched from the red light to the
green light,
send an instruction to one or more mobile device of the driver or to the
vehicle to
audibly or visually notify the driver that the one or more traffic signals is
a green light.
[150] An exemplary system may comprise an event data source comprising a
processor, a
transceiver, and first memory storing computer-executable instructions that,
when
executed by the processor, cause the event data source to: transmit, via the
transceiver
and to a vehicle and infrastructure computing device, information indicative
of an event
affecting a portion of road. The vehicle and infrastructure computing device
may
comprise a vehicle and infrastructure control computer, and second memory
storing
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computer-executable instructions that, when executed by the vehicle and
infrastructure
control computer, cause the vehicle and infrastructure computing device to
receive,
from the event data source, the information indicative of the event affecting
the portion
of road; determine one or more traffic devices associated with the portion of
road and
configured to control traffic for the portion of road; and based on the
information
indicative of the event affecting the portion of road, send, to the one or
more traffic
devices associated with the portion of road, instructions to change one or
more
characteristics of the one or more traffic devices.
[151] In some aspects, the one or more traffic devices may comprise a traffic
light having a
plurality of lights, and the one or more characteristics of the traffic light
may comprise
a timing of the plurality of lights.
[152] In some aspects, the one or more traffic devices may comprise a speed
limit display,
and the one or more characteristics of the speed limit display may comprise a
speed
limit displayed on the speed limit display.
[153] In some aspects, the information indicative of the event affecting the
portion of road
may comprise time information and information indicative of an estimate of a
number
of pedestrians associated with the event affecting the portion of road, and
the
information indicative of the event may be accessible from an electronic
calendar.
[154] In some aspects, the portion of road may comprise an intersection, and
the information
indicative of the event affecting the intersection may indicate that a number
of
pedestrians at the intersection will exceed a threshold number of pedestrians.
[155] In some aspects, the event may comprise an accident involving one or
more vehicles
affecting traffic flow through the portion of road. The one or more traffic
devices may
comprise one or more of a traffic light or a speed limit display. The
instructions to
change one or more characteristics of the one or more traffic devices may
comprise one
or more of instructions to increase a frequency of red lights at the traffic
light or
instructions to decrease a speed limit displayed on the speed limit display.
[156] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to, based on the information indicative of
the event
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affecting the portion of road, send, to one or more autonomous vehicles,
instructions to
take one or more actions in response to the event.
[157] In some aspects, the instructions to take one or more actions may
comprise an
instruction for the autonomous vehicle to apply brakes, an instruction for the
autonomous vehicle to slow down, or an instruction for the autonomous vehicle
to
speed up.
[158] In some aspects, the system may further comprise a pedestrian barrier
associated with
the portion of road. The second memory may store computer-executable
instructions
that, when executed by the vehicle and infrastructure control computer, cause
the
vehicle and infrastructure computing device to, based on the information
indicative of
the event affecting the portion of road, send, to the pedestrian barrier,
instructions to
activate the pedestrian barrier to prevent pedestrians from entering the
portion of road.
[159] In some aspects, the second memory may store computer-executable
instructions that,
when executed by the vehicle and infrastructure control computer, cause the
vehicle
and infrastructure computing device to, based on the information indicative of
the event
affecting the portion of road, send, to a mobile device of a pedestrian
located proximate
the portion of road, instructions for the mobile device to audibly or visually
notify the
pedestrian of the event affecting the portion of road.
[160] An exemplary vehicle and infrastructure computing device described
herein may
comprise a vehicle and infrastructure control computer, and memory storing
computer-
executable instructions that, when executed by the vehicle and infrastructure
control
computer, cause the vehicle and infrastructure computing device to: receive,
from an
event data source, information indicative of an event affecting a portion of
road;
determine one or more traffic devices associated with the portion of road and
configured
to control traffic for the portion of road; and based on the information
indicative of the
event affecting the portion of road, send, to the one or more traffic devices
associated
with the portion of road, instructions to change one or more characteristics
of the one
or more traffic devices.
[161] In some aspects, the one or more traffic devices may comprise a traffic
light having a
plurality of lights, and the one or more characteristics of the traffic light
may comprise
a timing of the plurality of lights.
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[162] In some aspects, the one or more traffic devices may comprise a speed
limit display,
and the one or more characteristics of the speed limit display may comprise a
speed
limit displayed on the speed limit display.
[163] In some aspects, the information indicative of the event affecting the
portion of road
may comprise time information and information indicative of an estimate of a
number
of pedestrians associated with the event affecting the portion of road, and
the
information indicative of the event may be accessible from an electronic
calendar.
[164] In some aspects, the portion of road may comprise an intersection, and
the information
indicative of the event affecting the intersection may indicate that a number
of
pedestrians at the intersection will exceed a threshold number of pedestrians.
[165] In some aspects, the event may comprise an accident involving one or
more vehicles
affecting traffic flow through the portion of road. The one or more traffic
devices may
comprise one or more of a traffic light or a speed limit display. The
instructions to
change one or more characteristics of the one or more traffic devices may
comprise one
or more of instructions to increase a frequency of red lights at the traffic
light or
instructions to decrease a speed limit displayed on the speed limit display.
[166] An exemplary method described herein may comprise receiving, at a
vehicle and
infrastructure computing device and from an event data source, information
indicative
of an event affecting a portion of road. The method may comprise determining
one or
more traffic devices associated with the portion of road and configured to
control traffic
for the portion of road. The method may comprise, based on the information
indicative
of the event affecting the portion of road, sending, to the one or more
traffic devices
associated with the portion of road, instructions to change one or more
characteristics
of the one or more traffic devices.
[167] In some aspects, the method may further comprise, based on the
information indicative
of the event affecting the portion of road, sending, to one or more autonomous
vehicles,
instructions to take one or more actions in response to the event.
[168] In some aspects, the method may further comprise, based on the
information indicative
of the event affecting the portion of road, sending, to a pedestrian barrier
associated
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with the portion of road, instructions to activate the pedestrian barrier to
prevent
pedestrians from entering the portion of road.
[169] In some aspects, the method may further comprise, based on the
information indicative
of the event affecting the portion of road, sending, to a mobile device of a
pedestrian
located proximate the portion of road, instructions for the mobile device to
audibly or
visually notify the pedestrian of the event affecting the portion of road.
[170] While the aspects described herein have been discussed with respect to
specific
examples including various modes of carrying out aspects of the disclosure,
those
skilled in the art will appreciate that there are numerous variations and
permutations
of the above described systems and techniques that fall within the spirit and
scope of
the invention.
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