eRSS-RAMP：一种基于扩展责任敏感安全的自动驾驶规则遵循运动规划器
eRSS-RAMP: A Rule-Adherence Motion Planner Based on Extended Responsibility-Sensitive Safety for Autonomous Driving
AI总结：
本文提出基于扩展责任敏感安全（eRSS）的规则遵循运动规划器 eRSS-RAMP，用于自动驾驶汇入与紧急避让场景，仿真显示其汇入长度缩短53.0%、汇入时间减少73.5%，并实现更稳定平滑的避撞路径。
摘要：
驾驶安全与责任判定是自动驾驶不可或缺的组成部分，它们也与路权分配和事故责任认定密切相关。为此，Intel/Mobileye 设计了责任敏感安全（RSS）框架，以进一步加强自动驾驶的安全规范，该框架以数学方式定义了自动驾驶车辆（AVs）在各种交通场景中的行为规则。然而，RSS 框架的规则在某些以交互不确定性为特征的场景中相对粗略，尤其是在紧急避撞期间需要协同驾驶的场景。此外，当前研究很少讨论 RSS 框架与运动规划的集成。因此，我们提出了一种基于扩展 RSS（eRSS）规范的规则遵循运动规划器（RAMP），用于非联网和联网自动驾驶车辆在汇入和紧急避让场景中的应用。仿真结果表明，所提出的方法能够实现更快、更安全的车道汇入性能（汇入长度缩短 53.0%，汇入时间减少 73.5%），并且在紧急避撞中允许更稳定的转向操作，从而为自车和周围车辆生成更平滑的路径。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
