Survey on artificial intelligence (AI) techniques for vehicular ad-hoc networks (VANETs)

A Mchergui, T Moulahi, S Zeadally - Vehicular Communications, 2022 - Elsevier
Advances in communications, smart transportation systems, and computer systems have
recently opened up vast possibilities of intelligent solutions for traffic safety, convenience …

Recent advances in reinforcement learning for traffic signal control: A survey of models and evaluation

H Wei, G Zheng, V Gayah, Z Li - ACM SIGKDD Explorations Newsletter, 2021 - dl.acm.org
Traffic signal control is an important and challenging real-world problem that has recently
received a large amount of interest from both transportation and computer science …

Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks

T Wu, P Zhou, K Liu, Y Yuan, X Wang… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
As urban traffic condition is diverse and complicated, applying reinforcement learning to
reduce traffic congestion becomes one of the hot and promising topics. Especially, how to …

Artificial intelligence for vehicle-to-everything: A survey

W Tong, A Hussain, WX Bo, S Maharjan - IEEE Access, 2019 - ieeexplore.ieee.org
Recently, the advancement in communications, intelligent transportation systems, and
computational systems has opened up new opportunities for intelligent traffic safety, comfort …

Fuzzy inference enabled deep reinforcement learning-based traffic light control for intelligent transportation system

N Kumar, SS Rahman, N Dhakad - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Intelligent Transportation System (ITS) has been emerged an important component and
widely adopted for the smart city as it overcomes the limitations of the traditional …

Applications of deep learning in intelligent transportation systems

AK Haghighat, V Ravichandra-Mouli… - Journal of Big Data …, 2020 - Springer
Abstract In recent years, Intelligent Transportation Systems (ITS) have seen efficient and
faster development by implementing deep learning techniques in problem domains which …

[HTML][HTML] Deep reinforcement learning for traffic signal control with consistent state and reward design approach

S Bouktif, A Cheniki, A Ouni, H El-Sayed - Knowledge-Based Systems, 2023 - Elsevier
Abstract Intelligent Transportation Systems are essential due to the increased number of
traffic congestion problems and challenges nowadays. Traffic Signal Control (TSC) plays a …

Deep reinforcement learning for traffic signal control: A review

F Rasheed, KLA Yau, RM Noor, C Wu, YC Low - IEEE Access, 2020 - ieeexplore.ieee.org
Traffic congestion is a complex, vexing, and growing issue day by day in most urban areas
worldwide. The integration of the newly emerging deep learning approach and the …

Distributed agent-based deep reinforcement learning for large scale traffic signal control

Q Wu, J Wu, J Shen, B Du, A Telikani… - Knowledge-based …, 2022 - Elsevier
Traffic signal control (TSC) is an established yet challenging engineering solution that
alleviates traffic congestion by coordinating vehicles' movements at road intersections …

Machine learning for security in vehicular networks: A comprehensive survey

A Talpur, M Gurusamy - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Machine Learning (ML) has emerged as an attractive and viable technique to provide
effective solutions for a wide range of application domains. An important application domain …