Impacts of automated vehicles on human-driving vehicle behaviors on highways: A Literature Review

The emergence of connected and automated vehicles (CAVs) and advanced communication technologies are believed to greatly alleviate traffic issues. However, it would be a long time before the CAVs reach a full market penetration rate, which means a mixed traffic flow of CAVs and traditional human-driving vehicles is inevitable and subsequent emerging issues may raise. Correspondingly, this study systematically reviews the literature on the impacts of the CAVs on the car-following, lane-changing, and merging behaviors of human-driving drivers on highways. This study is based on 42 key papers of the influence of driving behavior from Web Of Science and Science Direct in the last five years. The results show that the influence of the car-following behavior on human drivers is usually determined by the time headway (THW) and the car-following stability. The difference of lane-changing behavior is often studied by means of lane-changing gap and human driver’s perception. The literature on merging behavior mainly focuses on the merging efficiency of vehicles and the driver’s feeling. In addition, many studies have established a behavior model considering the interaction between two types of vehicles in a mixed flow scenario, which is the focus of current and future research. Besides, previously, virtual simulation and driving simulation are prevailing approaches for the study of impacts of CAVs, leaving the challenges of field test and validations under varying traffic and roadway situations, especially for the safety critical scenarios.