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.
Intelligent adaptive cruise control (IACC) systems have become a key technology for enhancing the safety and reliability of autonomous vehicles operating in dynamic traffic environments. This study proposes a fuzzy logic-based IACC architecture for collision avoidance that integrates longitudinal speed control, lateral...
Juan Carlos Suárez-Calderón, Iván Rocha-Gómez, O. Susarrey-Huerta et al.· International Journal of Aut...· 0 citations
A hybrid Fuzzy-Safety Model (FSM-H) that integrates longitudinal mitigation and lateral avoidance within a unified behavioral framework is proposed, providing a transparent and explainable human reference model suitable for simulation-based ADS safety benchmarking and regulatory assessment.
Research on automatic emergency braking (AEB) control algorithms for heavy
vehicles is relatively limited. Compared with passenger cars, heavy vehicle AEB
algorithms must accommodate both unloaded and fully loaded conditions, with the
latter posing higher demands. This study compares two distinct AEB control
strate...
Fei Lai, Chao-Qun Huang· SAE International Journal of...· 0 citations
Advancements in autonomous ground vehicle technology have led to widespread developments in the field. Autonomous ground vehicles require robust emergency stop systems capable of safely managing system failures without human intervention. This paper presents an intelligent emergency stop system that combines minimum-je...
K. Thompson, D. Bevly· SAE technical paper series· 0 citations
The multiple challenges of low adhesion roads, nonlinear dynamics and dynamic uncertainty present challenges for the decision making and control systems of autonomous vehicles in extreme traffic. This paper proposes a hierarchical coupling architecture: the upper layer uses a soft actor-critic (CSAC) algorithm with saf...
Shi-Cai Ji· International Workshop on Ar...· 0 citations