Title: Courteous MPC for Autonomous Driving with CBF-inspired Risk Assessment Show Chinese title

Title: 基于CBF启发的风险评估的礼貌MPC自动驾驶

Abstract: With more autonomous vehicles (AVs) sharing roadways with human-driven vehicles (HVs), ensuring safe and courteous maneuvers that respect HVs' behavior becomes increasingly important. To promote both safety and courtesy in AV's behavior, an extension of Control Barrier Functions (CBFs)-inspired risk evaluation framework is proposed in this paper by considering both noisy observed positions and velocities of surrounding vehicles. The perceived risk by the ego vehicle can be visualized as a risk map that reflects the understanding of the surrounding environment and thus shows the potential for facilitating safe and courteous driving. By incorporating the risk evaluation framework into the Model Predictive Control (MPC) scheme, we propose a Courteous MPC for ego AV to generate courteous behaviors that 1) reduce the overall risk imposed on other vehicles and 2) respect the hard safety constraints and the original objective for efficiency. We demonstrate the performance of the proposed Courteous MPC via theoretical analysis and simulation experiments. Show Chinese abstract

Abstract: 随着越来越多的自动驾驶车辆（AVs）与人工驾驶车辆（HVs）共享道路，确保安全且礼貌的行驶操作，尊重HVs的行为变得越来越重要。 为了在AV的行为中促进安全和礼貌，本文通过考虑周围车辆的噪声观测位置和速度，提出了一种基于控制屏障函数（CBFs）的扩展风险评估框架。 自我车辆感知的风险可以可视化为一个风险图，该图反映了对周围环境的理解，从而显示出促进安全和礼貌驾驶的潜力。 通过将风险评估框架整合到模型预测控制（MPC）方案中，我们提出了一个礼貌MPC，以生成礼貌行为，1）降低对其他车辆的整体风险，2）尊重硬性安全约束和原始效率目标。 我们通过理论分析和仿真实验展示了所提出的礼貌MPC的性能。