1. Accessing and Integrating CV and AV Sensor Data into Traffic Engineering Practice Dr. Jonathan Corey ITITS 2015 December 12, 2015 Chang’an, China

2. Outline Current Signal Timing Practice Sensors Data Processing Integration Into Practice Traffic Signal Control Systems 2

3. 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? 3

4. Outline Current Signal Timing Practice Sensors Data Processing Integration Into Practice Traffic Signal Control Systems 4

5. 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 5

6. 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.) 6

7. 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 7

8. Outline Current Signal Timing Practice Sensors Data Processing Integration Into Practice Traffic Signal Control Systems 8

9. 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 9

10. 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 10

11. 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 11 175 meters 22° arc 60 meters 90° arc

12. Sensors 12

13. 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 13

14. Outline Current Signal Timing Practice CV and AV Sensors Data Processing Integration Into Practice Traffic Signal Control Systems 14

15. 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 15

16. 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) 16

17. 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 17

18. 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) –… 18

19. 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 19

20. 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 20

21. 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 21

22. 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 22

23. Data Processing 23 CV2CV2 CV1CV1 CARCAR

24. 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 24

25. TRUCKTRUCK CARCAR Data Processing 25 CV2CV2 CV1CV1 CARCAR CV2CV2 CV1CV1 CV2CV2 CV1CV1 CARCAR

26. Outline Current Signal Timing Practice Sensors Data Processing Integration Into Practice Traffic Signal Control Systems 26

27. 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 27

28. 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 28

29. 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 29

30. 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 30

31. 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 31

32. Outline Current Signal Timing Practice Sensors Data Processing Integration Into Practice Traffic Signal Control Systems 32

33. 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 33

34. 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 34

35. 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 35

36. Traffic Signal Control Systems 36

37. 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 37

38. Questions? Jonathan Corey 796 Rhodes Hall 2850 Campus Way Dr. Phone: +1 513 556-6554 Email: jonathan.corey@uc.edu 38