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One challenging aspect of the Connected and Automated Vehicle (CAV) operationin mixed traffic is the development of a situation-awareness module for CAVs.While operating on public roads, CAVs need to assess their surroundings,especially the intentions of non-CAVs. Generally, CAVs demonstrate a defensivedriving behavior, and CAVs expect other non-autonomous entities on the roadwill follow the traffic rules or common driving behavior. However, the presenceof aggressive human drivers in the surrounding environment, who may not followtraffic rules and behave abruptly, can lead to serious safety consequences. Inthis paper, we have addressed the CAV and non-CAV interaction by evaluating asituation-awareness module for left-turning CAV operations in an urban area.Existing literature does not consider the intent of the following vehicle for aCAVs left-turning movement, and existing CAV controllers do not assess thefollowing non-CAVs intents. Based on our simulation study, the situation-awareCAV controller module reduces up to 27% of the abrupt braking of the followingnon-CAVs for scenarios with different opposing through movement compared to thebase scenario with the autonomous vehicle, without considering the followingvehicles intent. The analysis shows that the average travel time reductions forthe opposite through traffic volumes of 600, 800, and 1000 vehicle/hour/laneare 58%, 52%, and 62%, respectively, for the aggressive human driver followingthe CAV if the following vehicles intent is considered by a CAV in making aleft turn at an intersection.

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