Traffic accidents are one main cause of human fatalities in modern society. With the fast
development of connected and autonomous vehicles (CAVs), there comes both challenges …

This paper develops an integrated safety-enhanced reinforcement learning (RL) and model
predictive control (MPC) framework for autonomous vehicles (AVs) to navigate unsignalized …

This article concerns the open question of creating control policies of autonomous vehicles
(AVs) that lead to courteous motion. The study is built on a two-agent interaction between …

Connected and automated vehicles (CAVs) are expected to play a vital role in the next-
generation intelligent transportation system. In recent years, researchers have proposed …

The lane-changing decision-making process is challenging but critical to ensure safe and
smooth maneuvers for autonomous vehicles (AVs). Conventional Gipps-type algorithms lack …

In modern urban settings, automobile traffic and collisions lead to endless frustration as well
as significant loss of life, property, and productivity. Recent advances in artificial intelligence …

Abstract Connected and Automated Vehicles (CAVs) can potentially improve the
performance of the transportation system by reducing human errors. This paper investigates …

Localisation and navigation of autonomous vehicles (AVs) in static environments are now
solved problems, but how to control their interactions with other road users in mixed traffic …

In highway on-ramp sections, the conflictual interactions between a subject vehicle (merging
vehicle) in the acceleration lane and a following vehicle (lagging vehicle) in the adjacent …

With the consideration of personalized driving for automated vehicles (AVs), this paper
presents a human-like decision making framework for AVs. In the modelling process, the …