Collision Mitigation at Signalized Intersection Using Connected Vehicles Data and Technologies

Connected vehicle technology has shown great potential to improve traffic operations and safety. Intersections are among locations in urban areas with a high number of crashes between vehicles and pedestrians. This study utilizes the vehicle to vehicle (V2V), vehicle to infrastructure (V2I), and vehicle to pedestrian (V2P) communications to develop algorithms to predict unsafe conditions at signalized intersections, determine an appropriate crash remedial decision, and communicate it with appropriate vehicles. The proposed algorithms are examined in a simulation testbed developed in VISSIM under various demand patterns, connected vehicle penetration rates, and driver compliance with the crash remedial decisions. Case study results show that increasing the traffic demand and reducing driver compliance rate are associated with higher number of conflicts and potential crashes. Furthermore, increasing the market penetration rates is shown to be associated with less number of conflicts. Moreover, adding V2I communication to V2V and V2P communications helped decrease the number of conflicts significantly.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.
• Authors:
  • Tajalli, Mehrdad
  • Hajbabaie, Ali
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 6p

Subject/Index Terms

• TRT Terms: Algorithms; Case studies; Compliance; Connected vehicles; Crash risk forecasting; Drivers; Market penetration; Mobile communication systems; Signalized intersections; Simulation; Traffic volume
• Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01663087
• Record Type: Publication
• Report/Paper Numbers: 18-06418
• Files: TRIS, TRB, ATRI
• Created Date: Mar 20 2018 5:08PM