CAV-Based Intersection Maneuver Assist Systems (CAVIMAS) and Their Impact on Driver Behavior, Acceptance, and Safety

CAV-Based Intersection Maneuver Assist Systems (CAVIMAS) and Their
Impact on Driver Behavior, Acceptance, and Safety

Anuj Pradhan Headshot
Anuj K. Pradhan
Shan Bao Headshot
Shan Bao
Heejin Jeong Headshot
Heejin Jeong
UMTRI Logo

Principal Investigator(s):

Anuj K. Pradhan, Assistant Research Scientist – The University of Michigan Transportation Research Institute
Shan Bao, Associate Research Scientist – The University of Michigan Transportation Research Institute
Associate Professor – The University of Michigan-Dearborn
Heejin Jeong, Postdoctoral Research Fellow – The University of Michigan Transportation Research Institute

Project Abstract:
40% of the estimated 5.8 million crashes in the US in 2008 were intersection-related, with most of these having driver-related reasons attributed as the critical reasons for the crashes. Most of these human-related reasons have the potential to be mitigated by leveraging thoughtful deployments of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) safety management solutions in tandem with human factors based interventions relating to the content and presentation of such solutions. This project designed and experimentally evaluated a conceptual system – Connected and Automated Vehicle based Intersection Maneuver Assist Systems (CAVIMAS) – aimed at assisting drivers with intersection maneuvers by leveraging connected infrastructure and providing real-time guidance and warnings, and active vehicle controls. This was undertaken in an advanced driving simulation environment, and the system was evaluated via a user study to investigate drivers’ interactions with such systems, including their perceptions, acceptance, and trust-related behaviors.

Research Thrust(s): Enabling Technology

Project Form(s):
Project Information Form
Final Report Form