Lane-Changing Decision Model at Urban Tunnel Convergence Section Based on Multi-Source Information Fusion
Qian Xu, Fei Shao, Shaofeng Lin, Xintong Yan, Jingtao Wang · CICTP 2021 · 2021
The traffic lane-changing behavior at the convergence section of adjacent tunnel entrance and exit of urban expressway is a kind of micro driving environment with great randomness. The influencing factors include multi-source information like traffic flow conditions, road conditions, driving behavior characteristics and so on. In this paper, the mechanism of the influence of the information sources on the tunnel entrance is analyzed. Seven influencing factors of lane-changing decision, such as expected lane, driver’s temperament, traffic sign recognition, gap between vehicles of back side, fixation probability of interest area, speed difference between vehicles of front side and distance between vehicles of front side are ranked by analysis method of grey correlation entropy. Then, considering coupling of different drivers in the decision-making process of lane change, the driver’s lane-changing decision model is built based on multi-source information fusion.