With the rapid development of autonomous driving, the attention of academia has increasingly focused on the development of anti-collision systems in emergency scenarios, which have a crucial impact on driving safety. While numerous anti-collision strategies have emerged in recent years, most of them only consider steering or braking. The dynamic and complex nature of the driving environment presents a challenge to developing robust collision avoidance algorithms in emergency scenarios. To address the complex, dynamic obstacle scene and improve lateral maneuverability, this paper establishes a multi-level decision-making obstacle avoidance framework that employs the safe distance model and integrates emergency steering and emergency braking to complete the obstacle avoidance process. This approach helps avoid the high-risk situation of vehicle instability that can result from the separation of steering and braking actions. In the emergency steering algorithm, we define the collision hazard moment and propose a multi-constraint dynamic collision avoidance planning method that considers the driving area. Simulation results demonstrate that the decision-making collision avoidance logic can be applied to dynamic collision avoidance scenarios in complex traffic situations, effectively completing the obstacle avoidance task in emergency scenarios and improving the safety of autonomous driving.

翻译：随着自动驾驶技术的快速发展，学术界对紧急场景下防碰撞系统的关注日益增加，这些系统对驾驶安全具有关键影响。尽管近年来涌现出众多防碰撞策略，但多数仅考虑转向或制动操作。驾驶环境的动态复杂特性对开发紧急场景下的鲁棒碰撞规避算法提出了挑战。为解决复杂动态障碍物场景并提升横向机动能力，本文构建了一个基于安全距离模型的多层次决策避障框架，该框架整合紧急转向与紧急制动以完成避障过程。此方法有助于避免因转向与制动动作分离导致的车辆失稳高风险状况。在紧急转向算法中，我们定义了碰撞危险时刻，并提出了一种考虑行驶区域的多约束动态碰撞规避规划方法。仿真结果表明，该决策碰撞规避逻辑可应用于复杂交通场景中的动态避障场景，能有效完成紧急场景下的避障任务，并提升自动驾驶的安全性。