Connected and Automated Vehicle Based Intersection Maneuver Assist Systems (CAVIMAS) and Their Impact on Driver Behavior, Acceptance, and Safety

2020PDFTech ReportPradhan, Anuj K.Jeong, HeejinBao, ShanCenter for Connected and Automated Transportation (CCAT)University of Massachusetts at AmherstUniversity of Illinois at ChicagoUniversity of Michigan, DearbornUnited States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologyUnited States. Department of Transportation. University Transportation Centers (UTC) ProgramUniversity of Michigan. Center for Connected and Automated TransportationUnited StatesAutonomous vehiclesBehaviorConnected vehiclesDriver support systemsDriving simulatorsIntersectionsHuman factorsAutomated vehiclesUMTRI-2020-369A3551747105Final Report (May 2017 \u2013 April 2018)Intersection crashes can be potentially mitigated by leveraging deployments of vehicle-to-infrastructure (V2I) and vehicle-to- vehicle (V2V) safety management solutions. However, it is equally critical that these deployments are undertaken in tandem with interventions based on human factors evidence relating to the content and presentation of such solutions. This driving simulator study designed and 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. Results indicate that human factors considerations for the design and deployment of such systems remain paramount, given the findings related to drivers\u2019 trust and acceptance of these systems as measured via surveys and by examining actual driving behaviors.122