ITSC 2024 Paper Abstract

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Paper ThBT9.2

Chang, Yuan (Hunan University), Yang, Zeyu (Tsinghua University), Hu, Manjiang (Hunan University), Bian, Yougang (Hunan University), Li, Yang (State key laboratory of automotive safety and energy, Tsinghua U)

An Optimal Parking Path Planning Method Integrating Motion Mode Decision-Making for 4WIS Vehicles

Scheduled for presentation during the Regular Session "Motion planning" (ThBT9), Thursday, September 26, 2024, 14:50−15:10, Salon 17

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 14, 2024

Keywords Automated Vehicle Operation, Motion Planning, Navigation

Abstract

Four-wheel independent steering (4WIS) vehicles demonstrate high flexibility and maneuverability, rendering them as promising platforms for autonomous driving technologies. However, existing motion planning methods for 4WIS vehicles ignored their multiple motion modes, thus failing to fully leverage their excellent maneuver advantages in narrow scenarios. To address this issue, this paper proposes an optimal parking path planning integrating motion mode decision-making approach. Firstly, a coarse path planning is conducted based on the modified A* algorithm, facilitating the formulation and solution of the optimization problem. Then, a path planning-oriented simplified vehicle model is designed to reduce problem complexity and alleviate computational burden. Next, a switched affine system for multiple motion modes is constructed, and the logics associated with motion modes are introduced to formulate the parking path planning problem as a mixed-integer programming (MIP) task. Finally, the MIP is solved to obtain the optimal path and motion mode decisions simultaneously. Simulation results demonstrate that the proposed algorithm effectively leverages the flexibility and maneuverability advantages of 4WIS vehicles in parking scenarios.

 

 

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