[HTML][HTML] Artificial intelligence-based adaptive traffic signal control system: A comprehensive review

A Agrahari, MM Dhabu, PS Deshpande, A Tiwari… - Electronics, 2024 - mdpi.com
The exponential increase in vehicles, quick urbanization, and rising demand for
transportation are straining the world's road infrastructure today. To have a sustainable …

Adaptive network traffic control with approximate dynamic programming based on a non-homogeneous Poisson demand model

S Chen, X Lü - Transportmetrica B: Transport Dynamics, 2024 - Taylor & Francis
In this study, we develop a stochastic dynamic traffic-flow model subject to practical
restrictions under the non-homogeneous Poisson vehicle arrival process. Using the cell …

Improving the Urban Transport System Resilience Through Adaptive Traffic Signal Control Enabled by Decentralised Multiagent Reinforcement Learning

X Yang, Y Yu, Y Feng… - Journal of Advanced …, 2024 - Wiley Online Library
The principle of system resilience is its ability to withstand disruptions and maintain an
equilibrium state. In urban network systems, adaptive traffic signal control (ATSC) has been …

Collaborative Search Model for Lost-Link Borrowers Information Based on Multi-Agent Q-Learning

G You, H Guo, AA Dagestani, I Alnafrah - Axioms, 2023 - mdpi.com
To reduce the economic losses caused by debt evasion amongst lost-link borrowers (LBs)
and improve the efficiency of finding information on LBs, this paper focuses on the cross …

Cooperative Transit Signal Priority for the Arterial Road with Multi-Agent Reinforcement Learning to Reduce Schedule Delay

M Long, R Wang, J Chen, E Chung… - Available at SSRN … - papers.ssrn.com
Transit signal priority (TSP) is an effective operation strategy to decrease transit delays at
signalized intersections and improve their efficiency and reliability. With the great success of …