Synchronous Maneuver Searching and Trajectory Planning for Autonomous Vehicles in Dynamic Traffic Environments
Lilin Qian, Xin Xu, Yujun Zeng, Xiaohui Li, Zhenping Sun, and Hang, Song

TL;DR
This paper introduces a real-time algorithm for autonomous vehicle maneuver searching and trajectory planning in dynamic traffic, using topological concepts and heuristic optimization to ensure quick, feasible path generation.
Contribution
It proposes a novel SMSTP algorithm combining topological maneuver enumeration with trajectory profiles and corridor generation for synchronized planning.
Findings
Computation time less than 37ms per trajectory
Algorithm effectively handles dynamic traffic scenarios
Validated through simulation and real-world tests
Abstract
In the real-time decision-making and local planning process of autonomous vehicles in dynamic environments, the autonomous driving system may fail to find a reasonable policy or even gets trapped in some situation due to the complexity of global tasks and the incompatibility between upper-level maneuver decisions with the low-level lower level trajectory planning. To solve this problem, this paper presents a synchronous maneuver searching and trajectory planning (SMSTP) algorithm based on the topological concept of homotopy. Firstly, a set of alternative maneuvers with boundary limits are enumerated on a multi-lane road. Instead of sampling numerous paths in the whole spatio-temporal space, we, for the first time, propose using Trajectory Profiles (TPs) to quickly construct the topological maneuvers represented by different routes, and put forward a corridor generation algorithm based…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Autonomous Vehicle Technology and Safety · Robotics and Sensor-Based Localization
