Autonomous vehicles (AVs) can dramatically reduce the number of traffic crashes and associated fatalities by eliminating the avoidable human-error-related crash contributing factors. Many companies have been conducting pilot tests on public roads in several states in the U.S. and other countries to accelerate AV mass deployment. AV pilot operations on Californian public roads saw 251 AV-involved crashes (as of February 2020). These AV-involved crashes provide a unique opportunity to investigate AV crash risks in the mixed traffic environment. This study collected the AV crash reports from the California Department of Motor Vehicles and applied the decision tree and association rule methods to extract the pre-crash rules of AV-involved crashes. Extracted rules revealed that the most frequent types of AV crashes were rear-end crashes and predominantly occurred at intersections when AVs were stopped and engaged in the autonomous mode. AV and non-AV manufacturers and transportation agencies can use the findings of this study to minimize AV-related crashes. AV companies could install a distinct signal/display to inform the operational mode of the AVs (i.e., autonomous or non-autonomous) to human drivers around them. Moreover, the automatic emergency braking system in non-AVs could avoid a significant number of rear-end crashes as, often, rear-end crashes occurred as a result of the failure of following non-AVs to slow down in time behind AVs. Transportation agencies can consider separating AVs from non-AVs by assigning “AV Only” lanes to eliminate the excessive rear-end crashes resulting from the mistakes of human drivers in non-AVs at intersections.

Accurate and real-time traffic and road weather information acquired using connected vehicle (CV) technologies can help commuters perform safe and reliable trips. A nationwide survey of transit operation managers/supervisors was conducted to assess the suitability for CV transit applications in improving the safety and mobility during winter weather. Almost all respondents expressed positive attitudes towards the potential of CV applications in improving winter transit travel and voiced their concerns over the safety consequences of CV equipment failure, potential of increased driver distraction, and reliability of system performance in poor weather. A concept of operations of CV applications for multimodal winter travel was developed. In the conceptual framework, route-specific road weather and traffic flow data will be used by the transit managers/supervisors to obtain real-time operational status, forecast operational routes and schedules, and assess operational performance. Subsequently, multimodal commuters can receive the road-weather and traffic-flow information as well as transit routes and schedule information.