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Interactive Trajectory Planner for Mandatory Lane Changing in Dense Non-Cooperative Traffic

4 March 2023
Xiangguo Liu
Jianxing Chen
Shanmin Li
Yajia Zhang
Hongtao Yu
F. Huang
Jiechao Liu
Chao Wang
Liyun Li
Qi Zhu
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Abstract

When the traffic stream is extremely congested and surrounding vehicles are not cooperative, the mandatory lane changing can be significantly difficult. In this work, we propose an interactive trajectory planner, which will firstly attempt to change lanes as long as safety is ensured. Based on receding horizon planning, the ego vehicle can abort or continue changing lanes according to surrounding vehicles' reactions. We demonstrate the performance of our planner in extensive simulations with eight surrounding vehicles, initial velocity ranging from 0.5 to 5 meters per second, and bumper to bumper gap ranging from 4 to 10 meters. The ego vehicle with our planner can change lanes safely and smoothly. The computation time of the planner at every step is within 10 milliseconds in most cases on a laptop with 1.8GHz Intel Core i7-10610U.

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