Reinforcement learning has demonstrated its capability to solve challenging real-world
problems, ranging from autonomous driving to robotics and planning [1–12]. In some …

Bayesian optimization (BO) has established itself as a leading strategy for efficiently
optimizing expensive-to-evaluate functions. Existing BO methods mostly rely on Gaussian …

With the emergence of connected and automated vehicles (CAVs), understanding the
impact of such technological advances on traffic flow is vital to prepare for the popularity of …

Merging sections on highways are identified as traffic bottlenecks, leading to congestion and
accidents. The emergence of Connected and Autonomous Vehicles (CAVs) technology …

Ramp-merging zones have perennially served as bottlenecks for both safety and efficiency
within road traffic. Addressing the inherent uncertainties and anomalous behaviors …

Addressing safe and efficient interaction between connected and automated vehicles
(CAVs) and human-driven vehicles in a mixed-traffic environment has attracted considerable …

Reasonable mandatory lane-changing of vehicles in the vicinity of signalized intersections is
essential to traffic efficiency and vehicle safety at intersections. The negative impact of …

The rapid advancement of Vehicle-to-Everything communication (V2X) technology presents
opportunities for enhancing traffic energy efficiency. With V2X, this paper introduces an eco …

Network slicing has been considered as a promising candidate to meet the heterogeneous
Quality of Service (QoS) requirements of various vehicular applications. In this paper …

In this paper, we introduce a hierarchical decision-making framework for emerging mobility
systems. Despite numerous studies focusing on optimizing vehicle flow, practical feasibility …