LAUSR

Identifying and evaluating the potential risks in the surrounding environment is critical for intelligent vehicles’ safety and user experience. This paper provides a comprehensive overview of the state-of-the-art research on the surrounding vehicles’ lane change maneuver prediction and detection. First, various driver behavior modeling and classification methods are reviewed and analyzed, which gives a general understanding of what the lane change maneuver is and how to predict or detect the lane change maneuver. Next, the primary sensing devices equipped on intelligent vehicles and their impacts on lane change inference systems are discussed. Then, a series of representative research works in recent years are selected, introduced, and compared regarding their input feature selection, inference algorithms, and performance evaluation methods. Finally, some potential future research directions are proposed. This paper aims to help the relevant researchers and institutions summarize the current studies on the surrounding vehicles’ lane change maneuver inference and recognize its future development directions.