Recursive least-squares temporal difference learning for adaptive traffic signal control at intersection
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-3066-9
Abstract: This paper presents a new method to solve the scheduling problem of adaptive traffic signal control at intersection. The method involves recursive least-squares temporal difference (RLS-TD(λ)) learning that is integrated into approximate dynamic programming. The… read more here.
Keywords: intersection; traffic; traffic signal; adaptive traffic ... See more keywords
Bi-Level Optimization Model of Boundary Signal Control for the Network Based on Macroscopic Fundamental Diagrams
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Intelligent Transportation Systems Research"
DOI: 10.1007/s13177-019-00183-4
Abstract: This paper proposes a bi-level optimization model about boundary signal control for the network using macroscopic fundamental diagrams. Firstly, the road network is simplified as a directed graph, in which vertices and arcs respectively correspond… read more here.
Keywords: control; level optimization; model; optimization model ... See more keywords
Evaluating the impact of adaptive signal control technology on driver stress and behavior using real-world experimental data
Sign Up to like & getrecommendations! Published in 2018 at "Transportation Research Part F: Traffic Psychology and Behaviour"
DOI: 10.1016/j.trf.2018.06.006
Abstract: Abstract While the operational and crash reduction benefits of adaptive signal control technology (ASCT) have long been investigated, the impact of this technology on driver behavior and stress is still uncertain. This study evaluated the… read more here.
Keywords: adaptive signal; signal control; asct; driver stress ... See more keywords
A real-time signal control strategy for mitigating the impact of bus stops at urban signalized intersections
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Intelligent Transportation Systems"
DOI: 10.1080/15472450.2016.1194760
Abstract: ABSTRACT Buses stopping at transit stops reduce the capacity of signalized intersections, which can lead to excessive delays for all users. In order to avoid such phenomena, signal control strategies can be utilized. This article… read more here.
Keywords: signal control; bus; strategy; bus stop ... See more keywords
Cooperative Deep Q-Learning With Q-Value Transfer for Multi-Intersection Signal Control
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2907618
Abstract: The problem of adaptive traffic signal control in the multi-intersection system has attracted the attention of researchers. Among the existing methods, reinforcement learning has shown to be effective. However, the complex intersection features, heterogeneous intersection… read more here.
Keywords: cooperative deep; signal control; multi intersection; intersection ... See more keywords
Deep Reinforcement Learning for Traffic Signal Control: A Review
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3034141
Abstract: 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 traditional reinforcement learning approach has created an… read more here.
Keywords: reinforcement learning; deep reinforcement; signal control; traffic ... See more keywords
PlanLight: Learning to Optimize Traffic Signal Control With Planning and Iterative Policy Improvement
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3041441
Abstract: Intelligent traffic signal control (TSC) is essential for transportation efficiency in modern road networks. There is an emerging trend of using deep reinforcement learning techniques to train TSC models in simulators for reducing trial-and-error in… read more here.
Keywords: control; policy; algorithm; signal control ... See more keywords
A Novel Real-Time Traffic Signal Control Strategy for Emergency Vehicles
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3149920
Abstract: Intelligent traffic signal control strategies for emergency vehicles (EV) is a research hotspot in intelligent transportation systems. Its research results will promote the shortening of the travel time of EVs, which is vital to saving… read more here.
Keywords: time; traffic signal; signal control; traffic ... See more keywords
How Well Do Reinforcement Learning Approaches Cope With Disruptions? The Case of Traffic Signal Control
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3266644
Abstract: Data-driven and machine-learning-based methods are increasingly used in attempts to master the challenges of the world. But are they really the best approaches to manage complex dynamical systems? Our aim is to gain more insights… read more here.
Keywords: traffic signal; reinforcement learning; signal control; control ... See more keywords
A Novel Approach for Traffic Signal Control: A Recommendation Perspective
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Intelligent Transportation Systems Magazine"
DOI: 10.1109/mits.2017.2709779
Abstract: Traffic Signal Control is an effective mean of solving urban traffic problems by providing appropriate signal timings for road intersections. In this paper, we propose a novel approach originated from methods and applications of recommendation… read more here.
Keywords: signal control; traffic; traffic signal; novel approach ... See more keywords
A Comparison of Deep Reinforcement Learning Models for Isolated Traffic Signal Control
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Intelligent Transportation Systems Magazine"
DOI: 10.1109/mits.2022.3144797
Abstract: Traditional control methods may not be adaptive enough for ever-changing traffic dynamics. Hence, extensive deep reinforcement learning (DRL) methods have been utilized to solve the traffic signal timing control problem because DRL can adaptively learn… read more here.
Keywords: traffic signal; reinforcement learning; signal control; deep reinforcement ... See more keywords