With rapid population growth, there is an urgent need for intelligent traffic control techniques
in urban transportation networks to improve network performance. In an urban transportation …

An urban traffic light scheduling problem (UTLSP) is studied by using problem feature based
meta-heuristics with Q-learning. The goal is to minimize the network-wise total delay time …

In this paper, one type of heterogeneous traffic network, which consists of signalized
intersections and non-signalized ones, is analyzed and modelled with a macroscopic model …

This study addresses urban traffic light scheduling problem (UTLSP). A centralized model is
employed to describe the urban traffic light control problem in a scheduling framework. In the …

This paper presents a macroscopic model for pedestrian-vehicle mixed-flow network and a
traffic signal scheduling strategy for both pedestrians and vehicles. We first propose a novel …

This paper studies a large-scale urban traffic light scheduling problem (LUTLSP). A
centralized model is developed to describe the LUTLSP, where each outgoing flow rate is …

In this article, we consider a specific scenario, where multiple connected automated vehicles
(CAVs) entering one road link from different upstream links are required to form a platoon …

Computer vision-guided traffic management is an emerging area of research. Intelligent
traffic signal control using computer vision is a less explored area of research. In this paper …

Traffic congestion is a critical problem which makes roads busy. Traffic congestion
challenges traffic flow in urban areas. A growing urban area creates complex traffic …

In this paper, a novel centralized traffic network model is proposed to describe the urban
traffic light scheduling problem (UTLSP) in a traffic network. The objective is to minimize the …