In order to forward the development of transportation electrification and reach the goal of
carbon neutrality, eco-driving techniques for electric vehicles (EVs) are widely concerned …

Understanding and predicting highway lane-change maneuvers is essential for driving
modeling and its automation. The development of data-based lane-changing decision …

The development of autonomous transportation systems has received increasing attention
over the last decades. Different from existing automatic train control systems, the decision …

Predicting vehicle trajectories is crucial to ensuring automated vehicle operation efficiency
and safety, particularly on congested multi-lane highways. In such dynamic environments, a …

Fast and accurate long-term trajectory prediction of surrounding vehicles (SVs) is critical to
autonomous driving systems. In high-density traffic flows, strongly correlated vehicle …

Merge scenarios on highway are often challenging for autonomous driving, due to its lack of
sufficient tacit understanding on and subtle interaction with human drivers in the traffic flow …

Lane changes require dynamic decision-making and rapid behavior planning, which are
challenging for traffic modeling. We propose a two-dimensional following lane-changing …

Accuracy improvement of Car-following (CF) model has attracted much attention in recent
years. Although a few studies incorporate deep reinforcement learning (DRL) to describe CF …

Vehicle trajectory prediction is crucial and indispensable for ensuring the safe and efficient
operation of autonomous vehicles in complex traffic environments. The application of …

Merging behaviour is a fundamental yet challenging driving task which has significant
impact on traffic flow operations. While numerous efforts have been made on the modelling …