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VDOT’s Connected Vehicle Program
Noah Goodall, Ph.D., P.E.
Research Scientist
Virginia Center for Transportation Innovation and Research
ASHE Old Dominion Section Meeting
June 13, 2013 1
Smartphones
• Very sophisticated computer
• Sensors– GPS – 3-axis accelerometer– Camera– Magnetometer
• Carried with you all day
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Modern Vehicles – Very Sophisticated
• How many lines of code in a:– F-22 Raptor:– Average new Ford:
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1.7 million
10 million
Computerized Measurement
• Speed• Heading• Acceleration (lateral, longitudinal, vertical)• Position (from GPS)• Other diagnostics
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Vehicle-to-Vehicle Communication: Not Sophisticated
• Hi-tech vehicles
• Low-tech communication with other vehicles– Brake lights– Turn signals– Horn– Flash headlights
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Vehicle-to-Infrastructure Communication: Not Much Better
• We want to know where vehicles are, what they’re doing
• Many sensors already in the field to do this
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Field Detection
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Field Sensor Shortcomings
• Limited data quality
• Point detection, not continuous coverage
• Difficult/expensive to repair = frequent downtime
• Limited types of data– Aggregated speed, density, and volumes at a
single point
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Infrastructure-to-Vehicle
• Difficult to communicate with the driver both in real-time and across a wide area
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Connected Vehicles
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Wireless Vehicle Communication
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How it Works
• Transmit data from the vehicle– Captured from GPS, accelerometers,
magnetometers, or in-vehicle sensors
• Transmit to other vehicles or roadside equipment– Cellular, Bluetooth, WiMAX, Wi-Fi, DSRC
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Potential of Connected Vehicles
• Three ways to connect:1) Vehicle-to-vehicle:
• Electronic brake lights• Crash avoidance
2) Vehicle-to-infrastructure:• Incident detection• Weather/ice detection
3) Infrastructure-to-vehicle• Broadcast traffic signal timing• Dynamic re-routing
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Similarity to Other Safety Systems
• Similar to radar- and laser-based safety systems, but much cheaper
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Google Self-Driving Car
Adaptive Cruise Control
Connected Vehicles Today
• Real-time speed data from cell phones
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Research• VDOT is the lead state in the Cooperative
Transportation Systems Pooled Fund Study– Traffic signal control– Broadcasting traffic signal timing to approaching
vehicles– Potential of aftermarket add-on devices– Standardization– Pavement maintenance
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Connected Vehicle Test Bed
• University Transportation Centers grant for two small-scale field deployments of these technologies
• Will use combination of cellular and Dedicated Short-Range Communications (DSRC)– Low latency, high bandwidth– Allows for most powerful safety and mobility
applications17
Connected Vehicle Test Bed
• Partners:– VDOT– Virginia Tech– University of Virginia– Morgan State– Nissan and Volvo (advisory roles)
• Available to other universities to test projects
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Connected Vehicle Testbed
• Virginia Tech Smart Road – 7 RSUs
• Northern VA– 48 installed RSUs– 2 portable RSUs
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Roadside Units
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Roadside Units
Gallows Rd
I-66
US-50
US-29
I-495
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On Board Equipment
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On Board Equipment• 200 Aftermarket Safety
Devices are being developed • 10 instrumented cars
• 4 sedans (GM brand)• 2 SUVs (GM brand)• 4 motorcycles
• 2 instrumented heavy vehicles• Semi-truck• Motorcoach
• System offers Road Scout (Lane Detection), MASK (Head Tracker) and epoch detection
• Data is captured over the vehicle network (CAN)
• Parametric Data• Accel X,Y,Z• Gyro X,Y,Z• GPS Speed and Position• Network speed• Turn signal• Brake• Accelerator position
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Connected Vehicle Research Projects
• 19 projects have been funded that focus on freeway and arterial applications:
– Adaptive Stop/Yield – Adaptive Lighting– Intersection Management Using
Speed Adaptation – Eco-Speed Control – Awareness System for Roadway Workers – Emergency V2V Communication – Freeway Merge Management– Infrastructure Safety Assessment – Safety and Congestion Issues
Related to Public Transportation– Connected Motorcycle Crash Warning– Connected Motorcycle System Performance– Smartphone App Reducing Motorcycle and Bicycle Crashes
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– CV Freeway Speed Harmonization Systems– Reducing School Bus Conflicts through CVI– NextGen Transit Signal Priority with CVI– Smartphone DMS Application– Willingness to Pay and User Acceptance– Increasing Benefits at Low Penetration Rates
Background
• Rollout of connected vehicles will not be instantaneous
Projected rollout of on-board equipment in US Fleet (Volpe, 2008)
16 years between kickoff and 80%
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Connected Vehicle Applications
• Lots of connected vehicle mobility applications in development
• Most of these applications need at least 25% of vehicles to be “connected” to see benefits
• Higher percentages = more benefit
Application% Connected Vehicles Needed for Benefits
Traffic signal control 20-30%
Incident detection 20%
Queue length estimation 30%
Performance measurement 10-50%
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What it Means
• Problem – Mobile sensors and connected vehicle data are not constant or ubiquitous. There are gaps.
• Solution – “Location Estimation” – Behavior of equipped vehicles may suggest location
of unequipped vehicles.
Equipped VehiclesAssumed Location of Unequipped Vehicle
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Methodology
• How to estimate vehicle locations– Depends on unexpected behavior of equipped
vehicles – indicates an unequipped vehicle ahead
– What is “unexpected”?– Car-following model
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Algorithm
• Vehicles assumed to follow Wiedemann car-following model– Widely accepted, basis for VISSIM
• A deviation from expected acceleration indicates an unequipped vehicle ahead
Vehicle B
Speed = 45 mphAcceleration = 0 ft/s2
Speed = 30 mphAcceleration = -4 ft/s2
Expected Accel = 7 ft/s2
Vehicle A
Unexpected Behavior
Headway = 97 feet
Inserted Vehicle(Estimate)
Speed = 29 mphAcceleration = 0
Vehicle C
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Testing
• Using NGSIM datasets as ground truth– 30-minutes of individual
vehicle movements– ¼ mile segment of I-80 in
Emeryville, CA
• Designate some vehicles as “unequipped” and remove from data set
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Heat Map of Vehicle Densities
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4
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10
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0 200 400 600 800 1000 1200 1400 1600 1800
0
2
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0 200 400 600 800 1000 1200 1400 1600 1800
Densities Along I-80 at 25% Market Penetration
Actual Densities (Sampled and Observed Vehicles)
Estimated Densities (Sampled and Estimated Vehicles)
Time (s) 33
Ramp Metering Application
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Applied to Ramp Metering GAP Algorithm
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Summary
• Connected vehicles is important, innovative, and evolving
• VCTIR/VDOT is committed to being at the forefront
• Ensure that connected vehicles will meet the needs of Virginia
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