Although artificial intelligence has made tremendous progress recently, there remain various
technical issues and ethical problems before autonomous vehicles can be available to the …

This paper presents an interaction-aware motion planning and control framework for time-
critical traffic scenarios in which interaction with vehicles driven by humans is required. For …

In real traffic environment, a single control mode of traditional autonomous vehicles cannot
meet various driving requirements for different drivers, which will decrease the acceptance …

This paper proposes a novel driver-automation shared control based on a potential-field-
driven model predictive controller (PF-MPC) and a two-layer fuzzy strategy (TLFS) to …

As autonomous vehicles (AVs) become more prevalent on public roads, they will inevitably
interact with human-driven vehicles (HVs) in mixed traffic scenarios. To ensure safe …

A shared control of intelligent vehicles consists of a human driver and an automation to
complete the driving task. Through human-machine intelligence hybrid enhancement …

Car-following is an important driving behaviour for intelligent vehicles and has a significant
impact on traffic efficiency and traffic safety. Car-following models are widely developed to …

Agent-based modeling and simulation (ABMS) has been a popular approach to modeling
autonomous and interacting agents in a multi-agent system. Specifically, ABMS can be …

It is widely acknowledged that drivers should remain in the control loop of automated
vehicles before they completely meet real-world operational conditions. This paper …

In the past decade, reinforcement learning (RL) has achieved encouraging results in
autonomous driving, especially in well-structured and regulated highway environments …