自主赛车真实场景测试中的稳定性控制
Stability Control for Real World Testing in Autonomous Racing
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中文总结 AI 辅助
针对自主赛车无安全驾驶员、车辆易失稳的问题，提出含ESC、SC、CS的稳定性控制系统，经仿真与实车验证可维持稳定、扩展可运行区域，且提供开源实现。
中文摘要 AI 辅助
在极限操控状态下控制自动驾驶车辆是一项具有挑战性的任务。由于路面状况、天气等外部影响，车辆极易变得不稳定。大多数控制算法假设车辆行为稳定，因此在这些情况下可能失效。尤其是在自主赛车这类场景中，需操作昂贵车辆且无安全驾驶员随车，这构成了重大挑战。为实现车辆动态极限下的安全运行，本文提出一种综合稳定性控制系统，用于保障自动驾驶中的运动控制算法。该系统包含电子稳定控制（ESC）、滑移控制（SC）和反转向系统（CS），可协同调整运动控制器的转向与制动指令，以维持车辆稳定性。我们通过仿真及真实全尺寸车辆实验对该方法进行验证，结果表明该稳定性控制系统能在危急状况下维持车辆稳定性，并扩展了可运行区域。为简化集成，我们提供了开源实现，链接为this http URL。
英文摘要
Controlling an autonomous vehicle at the limits of handling is a challenging task. Due to external influences, such as road conditions or weather, a vehicle can easily become unstable. Since most control algorithms assume stable vehicle behavior, they might fail in these situations. Especially when operating expensive vehicles without a safety driver on board, as in autonomous racing, this poses a significant challenge. To enable safe operation at the vehicle's dynamic limits, we present a comprehensive stability control system that safeguards motion control algorithms in autonomous driving. The proposed system consists of an electronic stability control (ESC), a slip control (SC), and a countersteer system (CS), which collectively adapt steering and brake commands from the motion controller to maintain vehicle stability. We validate our approach through both simulation and experiments on a real-world, full-scale vehicle. The results show that the stability control system maintains vehicle stability in critical situations and extends the operational feasible region. To simplify integration, we provide an open-source implementation at github.com/TUMFTM/tam-stability-control.
发表机构
- Technical University of Munich（慕尼黑工业大学）
机构由 AI 辅助整理，请以论文原文为准。
