Safety assessment of vehicle traffic at signalized intersections using vehicle-to-infrastructure communication systems

Intersections are planned areas within the roadway infrastructure where conflicts between various roadway users may occur. Various strategies including traffic signals, markings, and roadway signs are used to control traffic movements along the potential conflict areas. Despite these control strategies, crashes between various road users within intersections have historically represented a large portion of overall roadway crashes. Safety assessment of signalized intersections has been a widely pursued research topic. A key challenge that current intersection traffic safety assessment methods face is the lack of high-fidelity data that can explain the pre-crash sequence of interactions between various road users. Recent advances in connected vehicle and vehicle-to-infrastructure communication technology have enabled the availability of new sources of high-fidelity and information-rich data. Connected vehicles broadcast their dynamic state information and connected intersections broadcast static information about the geometry of intersection's critical physical features along with their dynamic signal state information. When combined together, the information from these new data sources brings an opportunity to rethink current methods of intersection traffic safety assessment and develop new methods by combining classical approaches with modern approaches. This paper presents modern intersection traffic safety assessment methods that are built upon conflicts-based surrogate safety measures. The methods presented utilize the information from newly available data sources to reveal the probabilistic nature of safety critical zones within the intersection in both space and time. The results of these methods can enable transportation agencies to make informed decisions towards improving the intersection traffic safety.