9 papers
A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach
Jia Hu, Yang Chang, Haoran Wang
Motion planning for autonomous driving (AD) faces a critical trade-off. While traditional rule-based pipelines offer verifiable safety and interpretability, they often fail to gene…
Automated Driving with Evolution Capability: A Reinforcement Learning Method with Monotonic Performance Enhancement
Jia Hu, Xuerun Yan, Tian Xu +1
Reinforcement Learning (RL) offers a promising solution to enable evolutionary automated driving. However, the conventional RL method is always concerned with risk performance. The…
Anti-bullying Adaptive Cruise Control: A proactive right-of-way protection approach
Jia Hu, Zhexi Lian, Haoran Wang +6
Adaptive Cruise Control (ACC) systems have been widely commercialized in recent years. However, existing ACC systems remain vulnerable to close-range cut-ins, a behavior that resem…
Human-Machine Shared Control Approach for the Takeover of CACC
Haoran Wang, Zhexi Lian, Zhenning Li +5
Cooperative Adaptive Cruise Control (CACC) often requires human takeover for tasks such as exiting a freeway. Direct human takeover can pose significant risks, especially given the…
Vehicles Swarm Intelligence: Cooperation in both Longitudinal and Lateral Dimensions
Jia Hu, Nuoheng Zhang, Haoran Wang +3
Longitudinal-only platooning methods are facing great challenges on running mobility, since they may be impeded by slow-moving vehicles from time to time. To address this issue, th…
Safety-Aware Human-Lead Vehicle Platooning by Proactively Reacting to Uncertain Human Behaving
Jia Hu, Shuhan Wang, Yiming Zhang +3
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…