Safety-Aware Human-Lead Vehicle Platooning by Proactively Reacting to Uncertain Human Behaving
Jia Hu, Shuhan Wang, Yiming Zhang, Haoran Wang, Zhilong Liu, Guangzhi, Cao

TL;DR
This paper presents a safety-aware HL-CACC controller based on SMPC that predicts human driver intentions, improving safety and stability in vehicle platooning with real-time computational efficiency.
Contribution
It introduces a novel SMPC-based HL-CACC controller that proactively reacts to uncertain human driver behavior, enhancing safety and stability in platooning.
Findings
Improves perceived safety by 19.17% in oscillating traffic
Enhances safety against hard brakes by 7.76%
Achieves real-time performance with 3.2 ms computation time
Abstract
Human-Lead Cooperative Adaptive Cruise Control (HL-CACC) is regarded as a promising vehicle platooning technology in real-world implementation. By utilizing a Human-driven Vehicle (HV) as the platoon leader, HL-CACC reduces the cost and enhances the reliability of perception and decision-making. However, state-of-the-art HL-CACC technology still has a great limitation on driving safety due to the lack of considering the leading human driver's uncertain behavior. In this study, a HL-CACC controller is designed based on Stochastic Model Predictive Control (SMPC). It is enabled to predict the driving intention of the leading Connected Human-Driven Vehicle (CHV). The proposed controller has the following features: i) enhanced perceived safety in oscillating traffic; ii) guaranteed safety against hard brakes; iii) computational efficiency for real-time implementation. The proposed controller…
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Taxonomy
TopicsAutonomous Vehicle Technology and Safety
