ポテンシャル場と相互作用型速度最適化による自動運転車の経路計画
Potential Field-based Path Planning with Interactive Speed Optimization for Autonomous Vehicles
V2V通信で自車と周囲車両が局所経路を共有し、互いのポテンシャル場の影響を考慮した速度最適化により、合流場面での振動を抑えて安全性と快適性を向上させる手法を提案。
著者: Pengfei Lin, Ehsan Javanmardi, Jin Nakazato, Manabu Tsukada
分類: cs.RO
原文アブストラクト
Path planning is critical for autonomous vehicles (AVs) to determine the optimal route while considering constraints and objectives. The potential field (PF) approach has become prevalent in path planning due to its simple structure and computational efficiency. However, current PF methods used in AVs focus solely on the path generation of the ego vehicle while assuming that the surrounding obstacle vehicles drive at a preset behavior without the PF-based path planner, which ignores the fact that the ego vehicle's PF could also impact the path generation of the obstacle vehicles. To tackle this problem, we propose a PF-based path planning approach where local paths are shared among ego and obstacle vehicles via vehicle-to-vehicle (V2V) communication. Then by integrating this shared local path into an objective function, a new optimization function called interactive speed optimization (ISO) is designed to allow driving safety and comfort for both ego and obstacle vehicles. The proposed method is evaluated using MATLAB/Simulink in the urgent merging scenarios by comparing it with conventional methods. The simulation results indicate that the proposed method can mitigate the impact of other AVs' PFs by slowing down in advance, effectively reducing the oscillations for both ego and obstacle AVs.
