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Next-Generation Intersection Control Powered By Autonomous and Connected Vehicle Technologies

Next-Generation Intersection Control Powered By Autonomous and Connected Vehicle Technologies. Zhixia (Richard) Li, Ph.D. Assistant Professor Dept. of Civil & Environmental Engr. University of Louisville. All vehicles connected: It is law.

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Next-Generation Intersection Control Powered By Autonomous and Connected Vehicle Technologies

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  1. Next-Generation Intersection Control Powered By Autonomous and Connected Vehicle Technologies Zhixia (Richard) Li, Ph.D. Assistant Professor Dept. of Civil & Environmental Engr. University of Louisville

  2. All vehicles connected: It is law • In February of 2014, U.S. Transportation Secretary announced that the National Highway Traffic Safety Administration (NHTSA) has begun a rulemaking process and ultimately will mandate DSRC to be installed in all new cars and light trucks from 2016-2017.

  3. Communications Revolution Vehicle-Vehicle Communication (V2V) Vehicle-Infrastructure Communication (V2I) V2I plus V2V – V2X:Connected Vehicles

  4. V2V and V2I Communications • Dedicated Short Range Communications (DSRC) • Based on strengthened variant of consumer grade Wi-Fi know as IEEE 802.11p • Communication with adjacent vehicles and traffic controllers • Communication range: typically 1000 ft; can be up to 2500 ft • FCC assigned 5.850 to 5.925 GHz • Bandwidth = 75 MHz • DSRC has been widely tested for both V2V and V2I applications.

  5. Autonomous Vehicle Era is Coming Google Driverless Car • Autonomous Vehicle: capable of sensing its environment and navigating without human input • As of today Nevada, Florida, California, Michigan, and Washington D.C. have passed laws permitting autonomous cars. • Most auto manufacturers plan to sell their autonomous cars by 2017-2020.

  6. Agent-basedNext-Generation Intersection Control of Autonomous Vehicles • Traditional signalized intersection control • Limited capacity: not fully utilized intersection time space • Safety concern: 90% of the crashes occur on the roads are due to driver errors • Opportunity of Improvement • With availability of Autonomous Vehicle and Connected Vehicle technologies • How to use the technologies for maximizing intersection capacity is the key.

  7. Unused (Wasted) Intersection Resources in Signal Controlled Intersection (One left-turn vehicle occupying entire intersection) • Theory Behind: maximize the use of intersection time space • How to maximize: transfer conflicts between traffic movements to conflicts between individual vehicle.

  8. ACUTA: Autonomous Control of Urban TrAffic • Intersection mesh of n x n tiles (granularity) • V2I communication powered centralized control • Vehicle agent • Central intersection controller (CIC) • Reservation-based control algorithm • Turn from any lane

  9. Communicate • Centralized control algorithm • Step 1: Vehicle requesting reservation • Step 2: CIC processing a reservation request • Internal simulation to check conflicts • Minimum speed to allow fixed-speed reservation • Step 3: CIC declining and approving the reservation request CIC’s Internal Simulation n trials of different a

  10. Modeling vehicle central point position

  11. Modeling vehicle vertices positions

  12. Tile occupation by vehicle • Vectors representing edges of vehicle • V1 (PTHRPTHL), V2 (PTHLPTTL), V3 (PTTLPTTR), and V4 (PTTRPTHR) • A tile is considered being occupied if one of the following two conditions are met: • At least one vertex p(x0, y0) of the tile satisfies the following equation for every vector; or • At least on vertex p(x0, y0) of the vehicle rectangle satisfies the following equation.

  13. Trade-off between Mobility and Safety • Safety enhancement strategy • Safety buffer

  14. Modeled in Standard Simulation Platform: VISSIM • External Driver Model • Overriding the driver’s behavior models in VISSIM to realize centralized control

  15. Capacity Enhancing Strategies • Operational enhancement strategies • Advance Stop Location (ASL) • Non-Deceleration Zone (NDZ) • Priority Reservation (PR)

  16. Enhancement Strategies Evaluation • Evaluation of operational enhancement strategies • Under approach traffic demand 1050 veh/hr

  17. Effect of Granularity • Sensitivity analysis of granularity • Under approach traffic demand 1050 veh/hr

  18. Agent-basedNext-Generation Intersection Control of Autonomous Vehicles Granularity = 12 • Multi-tile ACUTA

  19. Operational Performance Evaluation • Multi-tile ACUTA vs. Optimized signal

  20. Operational Performance Evaluation • Operational Performance: Multi-tile ACUTA vs. Optimized signal

  21. Single-Tile ACUTA Approach Traffic Demand = 225 veh/hr • Single-tile ACUTA vs. 4-way stop control Single-tile ACUTA 4-way stop control

  22. Agent-basedNext-Generation Intersection Control of Autonomous Vehicles • Operational Performance: Single-tile ACUTA vs. 4-way stop control

  23. Evaluation of Sustainability Performance • Vehicle trajectories collected and output from simulation -VISSIM • Speed and acceleration rates were derived from the locations and times.

  24. Evaluation of Sustainability Performance • Operating mode distribution method of EPA’s MOVES Model • MOVES’ most accurate approach to estimate vehicle emission • Requires trajectory data at every second as input • Operating mode is based on VSP (vehicle specific power), vehicle speed.

  25. Evaluation of Sustainability Performance • Performance Measures • Total Pollutant Emission (g) • CO • PM2.5 • Total Energy Consumption (kj)

  26. Evaluation of Sustainability Performance • Emission: Multi-tile ACUTA vs. Optimized signal Approach Traffic Demand = 900 veh/hr/ln Approach Traffic Demand = 1800 veh/hr/ln

  27. Evaluation of Sustainability Performance • Energy consumption: Multi-tile ACUTA vs. Optimized signal Approach Traffic Demand = 900 veh/hr/ln Approach Traffic Demand = 1800 veh/hr/ln

  28. Evaluation of Sustainability Performance • Emission: Single-tile ACUTA vs. 4-way stop control Approach Traffic Demand = 225 veh/hr

  29. Evaluation of Sustainability Performance • Energy consumption: Single-tile ACUTA vs. 4-way stop control Approach Traffic Demand = 225 veh/hr

  30. Mixed Traffic:Tandem Signals with Flow Dispatching • Accommodation of human operated vehicles • Signal timing based on the market penetration rate of autonomous vehicles

  31. Related Journal Publications: • Li, Z., Chitturi, M.V., Yu, L., Bill, A.R. and Noyce, D.A.. (2015) “Sustainability Effects of “Sustainability Effects of Next-Generation Intersection Control for Autonomous Vehicles”, Transport, Taylor and Frances,30: 342-352. • Li, Z., Chitturi, M.V., Zheng, D., Bill, A.R. and Noyce, D.A. (2013). “Modeling Reservation-based Autonomous Intersection Control in VISSIM”, Transportation Research Record: Journal of Transportation Research Board, No. 2381, 81-90. • Li, Z., Chitturi, M.V., Zheng, D., Bill, A.R. and Noyce, D.A. (2015) “Capacity-Enhancing Intersection Control for Autonomous Vehicles – A Future Solution for Oversaturated Intersections”, Under review with Transportation Research Part C (revision submitted)

  32. Vision of Next Steps • Communication failure (simulating communications) • Incident management • Penalty for over speeding • Platoon scheduling • Pedestrians and Bicycles • Dynamic programming for system optimization • Emission-wise • Delay-wise • Energy consumption-wise • Mixed reality field testing • Can be scaled-down testing

  33. Thank You! &Questions and discussions?

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