公路安全自适应紧急制动:性能和可靠性评估的仿真框架

Ricardo Ribeiro, Catarina Gonçalves, Nuno Pombo
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引用次数: 0

摘要

公路安全是自动驾驶汽车的一个关键问题,特别是在需要精确制动和轨迹调整的动态和高风险场景下。本文对一种自动紧急制动(AEB)系统进行了综合评价,该系统旨在提高不同公路条件下的安全性。使用基于Matlab simulink的测试平台,研究了车对车后移动、车对车后静止和车对车后制动场景,遵循ISO 8855标准并利用3自由度(3DOF)车辆模型。分析强调了AEB系统通过自适应模型预测控制和动态路径规划来减轻碰撞的能力,确保安全高效的导航。结果表明,AEB系统在处理死锁、快速减速和复杂变道等挑战时,在平衡安全性和性能方面是有效的。尽管它具有优势,但也承认与现实世界的不可预测性和计算需求相关的局限性,并为未来的工作提供了改进与预测算法集成并增强可扩展性的建议。这项研究强调了先进AEB系统在提高公路驾驶安全性方面的重要性,并为评估其在模拟环境中的性能提供了一个强大的框架。通过解决当前研究中的关键空白,这项工作有助于开发更可靠、适应性更强的高速公路自动驾驶制动系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive emergency braking for highway safety: a simulation framework for performance and reliability evaluation

Highway safety is a critical concern for automated vehicles, particularly in dynamic and high-risk scenarios requiring precise braking and trajectory adjustments. This paper presents a comprehensive evaluation of an Automated Emergency Braking (AEB) system designed to enhance safety in diverse highway conditions. Using a Matlab Simulink-based test bench, the study explores Car-to-Car Rear Moving, Car-to-Car Rear Stationary, and Car-to-Car Rear Braking scenarios, adhering to ISO 8855 standards and leveraging a 3 Degrees of Freedom (3DOF) vehicle model.

The analysis highlights the AEB system’s ability to mitigate collisions through adaptive Model Predictive Control and dynamic Path Planning, ensuring safe and efficient navigation. Results demonstrate the AEB system’s effectiveness in handling challenges such as deadlocks, rapid deceleration, and complex lane-change scenarios while balancing safety and performance trade-offs. Despite its strengths, limitations related to real-world unpredictability and computational demands are acknowledged, with recommendations for future work to refine integration with predictive algorithms and enhance scalability.

This study underscores the importance of advanced AEB systems in improving highway driving safety and provides a robust framework for evaluating their performance in simulated environments. By addressing critical gaps in current research, this work contributes to the development of more reliable and adaptable braking systems for automated highway driving.

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