Connected & Automated Vehicles and Active Safety

Academia, industry, and government have been developing systems that simultaneously improve automotive safety and highway capacity for over 30 years. One approach toward improving vehicle safety incorporates sensors and computers that assume control over a vehicle, either in part or in whole. Connected vehicles can communicate with other vehicles and/or transportation infrastructure (such as traffic signals). There is a wide range of vehicle automation concepts, ranging from adaptive cruise control systems that only control a vehicles speed and following distance to fully automated systems that take on the entire dynamic driving task. California PATH has been involved in the research, development, and testing of connected and automated vehicles since its inception in 1986. 

Current Connected and Automated Vehicles Research

• Berkeley DeepDrive
• California Connected Vehicle Testbed 
• California Department of Motor Vehicles (DMV) Automated Vehicle Regulations
• Cooperative Adaptive Cruise Control
• Cooperative Intersection Collision Avoidance Systems  
• Creating Advanced Traffic Signal Controls Using Connected Vehicle Data
• Integrated Dynamic Transit Operation (IDTO) System Using Connected Vehicle Technologies
• Multi-Modal Intelligent Traffic Signal System
• Truck Platooning
• Using Cooperative ACC to Form High-Performance Vehicle Streams
• Vehicle Assist and Automation

Archive: Past Connected and Automated Vehicles Research

• Advanced Snowplow Project (ASP)
• Development of the Advanced Rotary Plow (ARP) for Snow Removal Operations 
• Integrated Collision Warning System
• National Automated Highways Systems Consortium
• Onboard Monitoring and Reporting for Commercial Motor Vehicle Safety
• Selected Mobility Applications for VII

Current Active Safety Research  

• Assessing Drivers’ Responses to Eco-driving Applications, PI: Peggy Wang; Description: Eco-driving applications are designed to change a person’s driving behavior by providing real-time, vehicle-specific information and advice such as to accelerate slowly and to reduce speed (to optimize vehicle speed, reduce fuel consumption, and reduce emissions). It is not known how effective real time information will be under dynamic traffic conditions. This project will investigate drivers’ responses when using eco-driving applications, the effects on fuel savings and emission reduction, and the associated safety impacts through a simulated driving experiment involving a local roadway with signalized intersections and freeway stop-and-go traffic. Project Sponsor: UCB-ITS SB-1; Funding: End Date: June 2021.

Archive: Past Active Safety Research

• Safety-Critical Requirements of External Communication for Automated Vehicle-Pedestrian Interactions, PI: Peggy Wang; Description: In this project, we will explore the interaction between highly automated vehicles and pedestrians. This project has the following objectives: identify safety critical scenarios of vehicle-pedestrian interaction, develop a prototype AV communication system for pedestrians, and experimentally evaluate the efficacy of the proposed AV communication systems. Project Sponsor: UCB-ITS SB-1; End Date: June 2019; Final Report:  https://escholarship.org/uc/item/82n7043g(link is external).
• User Acceptance and Public Policy Implications for Deployment of Automated Driving Systems, PI: Ching-Yao Chan; Description: The objective of this project is to understand public perception of ADS and to develop acceptance models that can help understand users’ intentions to use fully automated driving system, in all its forms. Findings from this study show that safety, vehicle control and compatibility, and trust are the three most critical factors that have influence on users’ acceptance of the fully automated driving systems. Project Sponsor: UCB-ITS SB-1; End Date: August 2018; Final Report: https://escholarship.org/uc/item/5570537f(link is external).