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REACT: Runtime-Enabled active collision-avoidance technique for autonomous driving
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DOI：10.1016/j.aei.2025.104248.png)
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Abstract
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Achieving rapid and effective active collision avoidance in dynamic interactive traffic remains a core challenge for autonomous driving. This paper proposes REACT (Runtime-Enabled Active Collision-avoidance Technique), a lightweight, closed-loop framework designed to unify risk assessment with interpretable active control. By leveraging energy transfer principles and human-vehicle–road interaction modeling, REACT dynamically quantifies runtime risk and constructs a spatially continuous risk field. The system incorporates physically grounded safety constraints such as directional risk and traffic rules to identify high-risk zones and generate interpretable avoidance behaviors. A hierarchical warning mechanism and lightweight runtime design ensure real-time responsiveness and onboard deployability. Evaluations across four representative high-risk scenarios including car-following braking, cut-in, rear-approaching, and intersection conflict demonstrate REACT’s capability to accurately identify critical risks and execute proactive avoidance. Its risk estimation aligns closely with human driver cognition (i.e., warning lead time < 0.4 s), achieving 100 % safe avoidance with zero false alarms or missed detections. Furthermore, it exhibits low-latency performance (< 50 ms latency), strong foresight, and generalization. The lightweight architecture achieves state-of-the-art accuracy, highlighting its potential for real-time deployment in safety–critical autonomous systems.
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