Inefficient traffic control is pervasive in modern urban areas, which would exaggerate traffic
congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we …

In the last few years, traffic congestion has become a growing concern due to increasing
vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that …

Observability and controllability are two critical requirements for a partially observable
transportation system. This paper proposes a stepwise signal optimization framework with …

Currently, one of the main challenges that large metropolitan areas must face is traffic
congestion. To address this problem, it becomes necessary to implement an efficient …

This study introduces a novel approach to adaptive traffic signal control (ATSC) by
leveraging multi-objective deep reinforcement learning (DRL) techniques. The proposed …

Sustainable management of traffic flows at signalized intersections is an important issue in
terms of traffic engineering. The minimization of lost time, emission, fuel consumption, etc …

Traffic signals may generate bottlenecks due to an unfair timing balance. Facing this
problem, adaptive traffic signal controllers have been proposed to compute the phase …

The problem of how to adjust speed of vehicles so that they can arrive at the intersection
when the light is green can be solved by means of Green Light Optimal Speed Advisory …

With an increasing number of vehicles on the road, demand for intelligent transportation
systems is on the rise. In this paper, we present a predictive road traffic management system …

Primary control parameters (eg, minimum and maximum green times) at actuated traffic
signal controllers are traditionally determined based on the limited historical or sample traffic …