基于扩展RSS的自动驾驶运动规划，提升变道与避撞安全性与效率。
eRSS-RAMP: A Rule-Adherence Motion Planner Based on Extended Responsibility-Sensitive Safety for Autonomous Driving
- 结合扩展RSS规则，设计可遵守交通责任规范的运动规划方法。
- 变道距离缩短53.0%，时间减少73.5%，避撞时转向更稳定。
- 适用于无通信与有通信自动驾驶，适合高安全要求场景。
驾驶安全与责任判定是自动驾驶不可或缺的组成部分，且与路权分配和事故责任认定密切相关。为此，Intel/Mobileye提出了责任敏感安全（RSS）框架，以数学方式定义自动驾驶车辆在各类交通场景下的行为规则。然而，在存在交互不确定性、尤其需协同避撞的紧急场景中，现有RSS规则仍显不足。此外，当前研究较少探讨将RSS框架与运动规划融合。为此，本文提出一种基于扩展RSS（eRSS）规则的规则遵从运动规划器（RAMP），适用于非联网与联网自动驾驶车辆在汇入及紧急避撞场景中的应用。仿真结果表明，所提方法可实现更快更安全的变道表现：变道长度缩短53.0%，变道时间减少73.5%；在紧急避撞中，路径更平滑，车辆转向更稳定，显著提升了自身及周围车辆的行驶平稳性。
原文摘要 · Abstract (English)
Driving safety and responsibility determination are indispensable pieces of the puzzle for autonomous driving. They are also deeply related to the allocation of right-of-way and the determination of accident liability. Therefore, Intel/Mobileye designed the responsibility-sensitive safety (RSS) framework to further enhance the safety regulation of autonomous driving, which mathematically defines rules for autonomous vehicles (AVs) behaviors in various traffic scenarios. However, the RSS framework's rules are relatively rudimentary in certain scenarios characterized by interaction uncertainty, especially those requiring collaborative driving during emergency collision avoidance. Besides, the integration of the RSS framework with motion planning is rarely discussed in current studies. Therefore, we proposed a rule-adherence motion planner (RAMP) based on the extended RSS (eRSS) regulation for non-connected and connected AVs in merging and emergency-avoiding scenarios. The simulation results indicate that the proposed method can achieve faster and safer lane merging performance (53.0% shorter merging length and a 73.5% decrease in merging time), and allows for more stable steering maneuvers in emergency collision avoidance, resulting in smoother paths for ego vehicle and surrounding vehicles.
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