Exploiting reinforcement learning (RL) for traffic congestion reduction is a frontier topic in
intelligent transportation research. The difficulty in this problem stems from the inability of the …

This paper presents a mathematical model for real-time queue estimation using connected
vehicle (CV) technology from wireless sensor networks. The objective is to estimate the …

Real-time estimation of the traffic state in urban signalized links is valuable information for
modern traffic control and management. In recent years, with the development of in-vehicle …

Owing to their dynamic and multidisciplinary characteristics, Unmanned Aerial Vehicles
(UAVs), or drones, have become increasingly popular. However, the civil applications of this …

Automated driving has become an important research trend in the field of cooperative
intelligent transportation systems and their applications in smart cities. Automated driving …

This paper develops estimators for market penetration level and arrival rate in finding queue
lengths from probe vehicles at isolated traffic intersections. Closed-form analytical …

During yellow intervals, dilemma zones (DZ) often trigger red light violations (RLV) and
unexpected stop**s near stop lines, causing severe collisions at signalized intersections …

Abstract The Connected Vehicle (CV) technology is a mobile platform that enables a new
dimension of data exchange among vehicles and between vehicles and infrastructure. This …

In this study, we develop a real-time estimation approach for lane-based queue lengths. Our
aim is to determine the numbers of queued vehicles in each lane, based on detector …

With the emergence of connected vehicle technology, the use of probe trajectory data to
estimate queue length has recently received considerable attention. Unlike data collected by …