Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …

Purpose-This paper aims to review the studies on intersection control with connected and
automated vehicles (CAVs). Design/methodology/approach-The most seminal and recent …

Reliable and efficient validation technologies are critical for the recent development of multi-
vehicle cooperation and vehicle-road-cloud integration. In this paper, we introduce our …

This paper presents a bibliographic and collaboration pattern analysis of the IEEE T
ransactions on I ntelligent V ehicles (T-IV). In this paper, a journal analysis framework is …

The development of connected and automated vehicles (CAVs) is the key to improving
urban mobility safety and efficiency. This article focuses on cooperative vehicle …

This work addresses the ecological-adaptive cruise control problem for connected electric
vehicles by a computationally efficient robust control strategy. The problem is formulated in …

The rapid evolution of vehicle-to-vehicle and vehicle-to-infrastructure communication opens
doors to various control algorithms, one particular domain being intersection control. Several …

We present a method for the signal-free path-free intersection control (SPIC) problem which
involves coordinating connected vehicles under automated driving (CVAD) at urban …

This paper introduces a novel centralized autonomous inclusive intersection management
mechanism (CAI 2 M 2) for heterogeneous connected vehicles (HCVs). The system …

Replacing traffic signals with roadside vehicle-to-infrastructure systems in the era of
connected and autonomous vehicles (CAVs) is promising. Managing CAVs in a signal-free …