Situation-Aware Left-Turning Connected and Automated Vehicle Operation at Signalized Intersections

One challenging aspect of the Connected and Automated Vehicle (CAV) operation in mixed traffic is the development of a situation awareness module for CAVs. While operating on public roads, CAVs need to assess the surrounding, especially intentions of non-CAVs. Generally, CAVs demonstrate a defensive driving behavior, and CAVs expect other non-autonomous entities on the road will follow the traffic rules or common driving norms. However, the presence of aggressive human drivers in the surrounding environment, who may not follow traffic rules and behave abruptly, can lead to serious safety consequences. In this paper, we have addressed the CAV and non-CAV interaction by evaluating a situation awareness module for left-turning CAV operations in an urban area. Existing literature does not consider the intent of the follower vehicle for a left-turning movement of a CAV, and existing CAV controllers do not assess intents of the follower non-CAVs. Based on our simulation study, the situation-aware CAV controller module reduces 40% of the abrupt braking of the follower non-CAVs for the scenario of 600 vphpl on the opposing through movement, compared to the base scenario with the autonomous vehicle without considering intents of the follower vehicles. For opposite through traffic volumes with 800 and 1000 vphpln, the reduction decreases to 10%. The analysis shows that the average travel time reductions for the opposite through traffic volumes of 600, 800 and 1000 vphpln are 61%, 23%, and 41%, respectively, for the follower non-CAV if the intent of the follower vehicle is considered by a CAV in making a left turn at an intersection.