accessing and integrating cv and av sensor data into traffic engineering practice dr. jonathan corey...
DESCRIPTION
Challenge Conventional traffic signal control systems will be in use for decades Most current traffic signal research assumes 100% CV or AV populations Current projections put AV adoption at 75% in 2040 How can we improve current traffic signal system performance with CV/AV data? 3TRANSCRIPT
Accessing and Integrating CV and AV Sensor Data into
Traffic Engineering Practice
Dr. Jonathan CoreyITITS 2015
December 12, 2015Chang’an, China
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Outline
• Current Signal Timing Practice• Sensors• Data Processing• Integration Into Practice• Traffic Signal Control Systems
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Challenge
• Conventional traffic signal control systems will be in use for decades
• Most current traffic signal research assumes 100% CV or AV populations
• Current projections put AV adoption at 75% in 2040
• How can we improve current traffic signal system performance with CV/AV data?
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Outline
• Current Signal Timing Practice• Sensors• Data Processing• Integration Into Practice• Traffic Signal Control Systems
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Current Signal Timing Practice
• United States Department of Transportation– Recommends retiming traffic signals every 3
years• Ohio State Department of Transportation
– Traffic signals retimed every 3-6 years– Typically using 24-72 hour counts – Data is frequently processed to peak hour
turning counts
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Current Signal Timing Practice
• The current availability of data is driven by data collection intervals and operational requirements– Operations sensors tend to have small
detection areas (loop detector, camera, etc.)– Traffic counts are generally taken with
temporary equipment (tube counter, radar, etc.)
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Current Signal Timing Practice
• Conventional systems will be in use for decades
• Algorithms to translate CV and AV data into traffic signal timing plans are needed– Data will be available in real-time compared to
occasional collection– Data quality will depend on vehicle
make/model, sensor type, and number of CV/AVs in the area
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Outline
• Current Signal Timing Practice• Sensors• Data Processing• Integration Into Practice• Traffic Signal Control Systems
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Sensors
• For traffic signal control– CVs have generally been seen as probe
vehicles sending back data such as• Position• Speed• Hazard messages
– AV behaviors have been modeled as either• Reading existing and obeying signals• Actively managed participants in the traffic control
system
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Sensors
• There are many sensors on production cars that can generate useful data– Adaptive cruise control (ACC) uses a radar to
detect collision hazards ahead of the vehicle– Rear-end and blind spot detection (BSD) uses
radar and ultrasonic sensors • AVs will use radar and lidar to scan their
surroundings for collision hazards
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Sensors• The Delphi Electronic Scanning
Radar (ESR) is a common sensor for ACC
• The ESR detects vehicles, pedestrians and obstacles
• The ESR is effectively two radars in the same unit– 60m range with 90° arc– 175m range with 22° arc
175 meters22° arc
60 meters90° arc
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Sensors
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Sensors
• Vehicles with ACC and BSD systems are currently on the road
• CV systems become mandatory in USA on new vehicles soon
• Some CVs will come with ACC and/or BSD from the very beginning
• This means we could begin collecting data from selected CVs from the very beginning
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Outline
• Current Signal Timing Practice• CV and AV Sensors• Data Processing• Integration Into Practice• Traffic Signal Control Systems
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Data Processing
• Data processing in a CV, AV and traffic signal control system context is complex
• Processing can occur at multiple points and to multiple degrees
• Data storage is another challenge• Overlapping needs and requirements may
mandate processing, storage, and transmission locations
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Data Processing
• Start with what we need– Sensing vehicle location, speed, and direction– Vehicle type, sensor type and field of view
(horizontal and vertical)– Location, speed and direction of detected
vehicles• Additional data we want
– Light status (if the vehicle has a camera)– Video (when queried)
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Data Processing
• CV systems are both designed to send back their own position, speed, and location
• Sensor types and metadata are very simple to store or transmit– Central database– Short query and message through CV system
• So far, it looks easy
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Data Processing
• Where do we process the sensor data to determine the location, speed and direction of other vehicles?
• There are several options– Central computer– Traffic signal control system– Within the vehicle (in sensor and/or computer) – …
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Data Processing
• If we process the data at a central location– We will need to have very large and fast
communications links– The processed data will still need to be sent
to the traffic signal control system– Algorithms to translate processed data into
traffic signal control data are needed– Failure at the central processing node will kill
the entire system
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Data Processing
• Processing the data at the traffic signal control system– Requires allocation of CV/AV communications
to the proper traffic signal control system– Communication volume is still potentially high– Current traffic signal control systems are not
high performance computing systems– Each traffic signal system will need its own
algorithms to be developed
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Data Processing
• Processing data on the vehicle– Sensor data volumes are small– Processing power is limited– Dedicated processing hardware can be used– Only one set of sensor types and one
configuration need to be considered– Lower communication requirements to
transmit processed data– AVs will be processing data locally
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Data Processing
• Assuming raw data processing occurs on vehicle, we still have work to do– Processed data is not perfect data– Two different CVs/AVs may show a detected
vehicle in different locations due to• Sensor error and bias• Angle measurement was taken from• Time discrepancies
Data Processing
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CV2
CV1
CAR
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Data Processing
• The final data processing step will need to be at either a central computer or at the traffic signal control system
• A model based approach will allow constraints to be used – Vehicle conservation between detections– Predicted location of previously detected
vehicles
TRUCK C
AR
Data Processing
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CV2
CV1
CAR
CV2
CV1
CV2
CV1
CAR
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Outline
• Current Signal Timing Practice• Sensors• Data Processing• Integration Into Practice• Traffic Signal Control Systems
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Integration into Practice
• Current practice does not use generally use real-time data
• Conventional systems are retimed on multiple year time scales
• Planning of new intersections is slower• Incident detection is one of the few areas
current practice uses real-time information
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Integration into Practice
• Some traffic signal control systems use near real-time data for operations– Adaptive and traffic responsive systems
frequently aggregate data to the cycle– Many systems offer reporting services current
to the last cycle• Data output from traffic signal control
systems can be problematic
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Integration into Practice
• Many of the potential benefits of real-time data collection are discarded– Real-time data requires large storage– Reported data and measures are obsolete– Personnel are not trained in computer
operations• Database operations• Visualization of data• Modeling software
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Integration into Practice
• The biggest required changes are institutional– Personnel need to have significantly stronger
and varied computer skills– Data and processes need to focus on
disaggregation• Stop treating every day of the year as though it
were the same• There are many more events in a day than practice
currently acknowledges
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Integration into Practice
• CV and AV systems offer tremendous opportunities to advance the practice
• Looking at history, there will be a chicken and egg problem– Will new data drive new reporting and
standards?– Will new standards drive data collection?
• Either solution has its own challenges
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Outline
• Current Signal Timing Practice• Sensors• Data Processing• Integration Into Practice• Traffic Signal Control Systems
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Traffic Signal Control Systems
• Current traffic signal control systems are not designed to incorporate CV/AV data
• New systems, or extensions of existing systems, will need to be developed
• Current systems are generally reacting to past information
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Traffic Signal Control Systems
• To operate during the transition from conventional vehicles to CVs and AVs– Traffic signal systems need to incorporate CV
and AV data into their optimization algorithms– These systems should function seamlessly
from 0% to 100% CVs and AVs• Separate the data processing
– Model of the area– Traffic signal control
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Traffic Signal Control Systems
• The model portion of the traffic signal control system– Estimates the positions of previously detected
vehicle– Is simple to reduce computation and data
loads– Can replace estimated vehicle data with
CV/AV reported data
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Traffic Signal Control Systems
Accelerate
DecelerateQueue
Cruise
Obstruction
Stopped
GreenLight
Reached Desired Speed
Increased SpeedLimit
ClearedObstruction
RedLight
RedLight
ObstructionGreenLight
ClearedObstruction
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Traffic Signal Control Systems
• With the underlying model we can run any kind of traffic signal control system– Current systems could be run via emulation– New systems
• New system models can also be implemented– Reservation based systems– Cooperative traffic signals
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Questions?
Jonathan Corey796 Rhodes Hall2850 Campus Way Dr.Phone: +1 513 556-6554Email: [email protected]