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arXiv · 2503.05471

Topology-Driven Trajectory Optimization for Modelling Controllable Interactions Within Multi-Vehicle Scenario

Changjia Ma·Yi Zhao·Zhongxue Gan·Bingzhao Gao·Wenchao Ding
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Abstract

Trajectory optimization in multi-vehicle scenarios faces challenges due to its non-linear, non-convex properties and sensitivity to initial values, making interactions between vehicles difficult to control. In this paper, inspired by topological planning, we propose a differentiable local homotopy invariant metric to model the interactions. By incorporating this topological metric as a constraint into multi-vehicle trajectory optimization, our framework is capable of generating multiple interactive trajectories from the same initial values, achieving controllable interactions as well as supporting user-designed interaction patterns. Extensive experiments demonstrate its superior optimality and efficiency over existing methods. We will release open-source code to advance relative research.

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Changjia Ma, Yi Zhao, Zhongxue Gan, Bingzhao Gao, Wenchao Ding. 2025-03-07. Topology-Driven Trajectory Optimization for Modelling Controllable Interactions Within Multi-Vehicle Scenario. https://arxiv.org/abs/2503.05471

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