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https://doi.org/10.1145/3292500.3330949
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4614-6243-9_2openalex-snapshot
The Max-Pressure Controller for Arbitrary Networks of Signalized Intersections
inferredcites →https://doi.org/10.1007/978-3-319-25808-9openalex-snapshot
Autonomic Road Transport Support Systems
inferredcites →https://doi.org/10.1016/j.engappai.2013.01.007openalex-snapshot
Holonic multi-agent system for traffic signals control
inferredcites →https://doi.org/10.1016/j.ifacol.2016.10.366openalex-snapshot
Adaptive Max Pressure Control of Network of Signalized Intersections
inferredcites →https://doi.org/10.1016/j.trc.2006.05.001openalex-snapshot
The real-time urban traffic control system CRONOS: Algorithm and experiments
inferredcites →https://doi.org/10.1016/j.trc.2013.08.014openalex-snapshot
Max pressure control of a network of signalized intersections
inferredcites →https://doi.org/10.1038/nature14236openalex-snapshot
Human-level control through deep reinforcement learning
inferredcites →https://doi.org/10.1049/iet-its.2009.0070openalex-snapshot
Reinforcement learning-based multi-agent system for network traffic signal control
inferredcites →https://doi.org/10.1061/(asce)0733-947x(2003)129:3(278)openalex-snapshot
Reinforcement Learning for True Adaptive Traffic Signal Control
inferredcites →https://doi.org/10.1109/itsc.2010.5625066openalex-snapshot
An agent-based learning towards decentralized and coordinated traffic signal control
inferredcites →https://doi.org/10.1109/jas.2016.7508798openalex-snapshot
Traffic signal timing via deep reinforcement learning
inferredcites →https://doi.org/10.1109/tits.2013.2255286openalex-snapshot
Multiagent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC): Methodology and Large-Scale Application on Downtown Toronto
inferredcites →https://doi.org/10.1145/3219819.3220096openalex-snapshot
IntelliLight
inferredcites →https://doi.org/10.1145/3308558.3314139openalex-snapshot
CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
inferredcites →https://doi.org/10.1145/3357384.3357900openalex-snapshot
Learning Phase Competition for Traffic Signal Control
inferredcites →https://doi.org/10.1287/trsc.31.1.5openalex-snapshot
Controlled Optimization of Phases at an Intersection

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4152865openalex-extracted
Emvlight: A Multi-Agent Reinforcement Learning Framework for an Emergency Vehicle Decentralized Routing and Traffic Signal Control System
inferred← citeshttps://doi.org/10.2139/ssrn.4186584openalex-extracted
inferred← citeshttps://doi.org/10.2139/ssrn.4186588openalex-extracted
Ped-Mp: A Pedestrian-Friendly Max-Pressure Signal Control Policy for City Networks
inferred← citeshttps://doi.org/10.2139/ssrn.4413739openalex-extracted
inferred← citeshttps://doi.org/10.2139/ssrn.4598461openalex-extracted
Democratizing Traffic Control in Smart Cities
inferred← citeshttps://doi.org/10.2139/ssrn.4669175openalex-extracted
Research on Max Pressure Signal Control Method for Collaborative Optimization of Motor Vehicles and Non-Motor Vehicles
inferred← citeshttps://doi.org/10.2139/ssrn.4760719openalex-extracted
A Universal Offline Reinforcement Learning Model for Adaptive Traffic Signal Control at Heterogeneous Intersections
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Learning to Simulate on Sparse Trajectory Data
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Learning Cooperative Max-Pressure Control by Leveraging Downstream Intersections Information for Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-3-030-86514-6_29openalex-snapshot
Multi-agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-3-030-94662-3_7openalex-snapshot
MARL for Traffic Signal Control in Scenarios with Different Intersection Importance
inferred← citeshttps://doi.org/10.1007/978-3-031-12423-5_16openalex-snapshot
EcoLight: Eco-friendly Traffic Signal Control Driven by Urban Noise Prediction
inferred← citeshttps://doi.org/10.1007/978-3-031-20179-0_7openalex-snapshot
Multi-agent Traffic Signal Control via Distributed RL with Spatial and Temporal Feature Extraction
inferred← citeshttps://doi.org/10.1007/978-3-031-33377-4_27openalex-snapshot
Multi-Agent Meta-Reinforcement Learning with Coordination and Reward Shaping for Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-3-031-40286-9_22openalex-snapshot
Spatial-Temporal Diffusion Probabilistic Learning for Crime Prediction
inferred← citeshttps://doi.org/10.1007/978-3-031-43430-3_9openalex-snapshot
Leveraging Queue Length and Attention Mechanisms for Enhanced Traffic Signal Control Optimization
inferred← citeshttps://doi.org/10.1007/978-3-031-67447-1_2openalex-snapshot
Fair and Efficient Traffic Light Control with Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-70819-0_14openalex-snapshot
Reinforcement Learning-Based Cooperative Traffic Control System
inferred← citeshttps://doi.org/10.1007/978-3-031-86370-7_12openalex-snapshot
Reinforcement Learning Algorithms with Graph Convolution Networks for Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-3-032-10489-2_37openalex-snapshot
Inverse Reinforcement Learning for Reward Function in Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-3-032-33185-4_2openalex-snapshot
Multi-agent Learning for Multi-intersection Traffic Control with a Swarm of Drones
inferred← citeshttps://doi.org/10.1007/978-3-032-37670-1_17openalex-snapshot
DataLight: Data-Centric Offline Reinforcement Learning for Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-981-92-3441-7_26openalex-snapshot
Counterfactual Trajectory Augmentation for Data-Efficient Reinforcement Learning in Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-981-95-3358-9_20openalex-snapshot
A Real-Time Adaptive Traffic Signal Control Framework Using Graph Neural Networks and Multi-Agent Reinforcement Learning with Crowdsourced Event Integration
inferred← citeshttps://doi.org/10.1007/978-981-95-4960-3_16openalex-snapshot
Graph-Attention Policy Gradient Framework for Adaptive Traffic Signal Control in Complex Urban Networks
inferred← citeshttps://doi.org/10.1007/978-981-96-9894-3_7openalex-snapshot
HMLight: Hierarchical Multi-Agent Deep Reinforcement Learning with Long-Short-Term Planning in Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-981-97-3682-9_20openalex-snapshot
Adaptive Signal Control for Multiple Urban Road Intersections
inferred← citeshttps://doi.org/10.1007/978-981-99-8082-6_5openalex-snapshot
Interactive Attention-Based Graph Transformer for Multi-intersection Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/978-981-99-9640-7_1openalex-snapshot
Explicit Coordination Based Multi-agent Reinforcement Learning for Intelligent Traffic Signal Control
inferred← citeshttps://doi.org/10.1007/s10115-023-01938-yopenalex-snapshot
EcoLight+: a novel multi-modal data fusion for enhanced eco-friendly traffic signal control driven by urban traffic noise prediction
inferred← citeshttps://doi.org/10.1007/s10462-025-11340-5openalex-snapshot
Multi-agent reinforcement learning for resources allocation optimization: a survey
inferred← citeshttps://doi.org/10.1007/s10462-026-11530-9openalex-snapshot
Intelligent traffic signal control based on reinforcement learning: a survey
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A review of cooperative multi-agent deep reinforcement learning
inferred← citeshttps://doi.org/10.1007/s10489-023-04652-yopenalex-snapshot
A multi-agent reinforcement learning method with curriculum transfer for large-scale dynamic traffic signal control
inferred← citeshttps://doi.org/10.1007/s10489-023-05197-wopenalex-snapshot
RELight: a random ensemble reinforcement learning based method for traffic light control
inferred← citeshttps://doi.org/10.1007/s10489-025-06359-8openalex-snapshot
DiffusionLight:a multi-agent reinforcement learning approach for traffic signal control based on shortcut-diffusion model
inferred← citeshttps://doi.org/10.1007/s10489-025-06758-xopenalex-snapshot
Multi-agent neighborhood coordinated and holistic optimized actor-critic framework for adaptive traffic signal control
inferred← citeshttps://doi.org/10.1007/s10489-026-07336-5openalex-snapshot
Multi-agent graph reinforcement learning for real-time traffic signal control with spatio-temporal awareness
inferred← citeshttps://doi.org/10.1007/s10489-026-07487-5openalex-snapshot
BootDiffLights: Decentralized traffic signal control via diffusion-based reward generation
inferred← citeshttps://doi.org/10.1007/s10586-026-06275-7openalex-snapshot
Optimized adaptive traffic management using double DQN and prioritized experience replay in a multi-agent traffic control setup
inferred← citeshttps://doi.org/10.1007/s10994-023-06412-yopenalex-snapshot
Libsignal: an open library for traffic signal control
inferred← citeshttps://doi.org/10.1007/s10994-025-06785-2openalex-snapshot
FLight: optimization algorithm for traffic lights based on short-term traffic state forecast
inferred← citeshttps://doi.org/10.1007/s11042-024-20060-xopenalex-snapshot
Urban traffic signal control optimization through Deep Q Learning and double Deep Q Learning: a novel approach for efficient traffic management
inferred← citeshttps://doi.org/10.1007/s11227-024-06047-3openalex-snapshot
Dual experience replay-based TD3 for single intersection signal control
inferred← citeshttps://doi.org/10.1007/s11761-026-00503-zopenalex-snapshot
Deep reinforcement learning-based adaptive traffic signal control in urban networks
inferred← citeshttps://doi.org/10.1007/s13042-024-02190-8openalex-snapshot
Open-ti: open traffic intelligence with augmented language model
inferred← citeshttps://doi.org/10.1007/s13042-025-02864-xopenalex-snapshot
DCA2C: Dynamic cooperative A2C-based traffic signal control in multi-intersection environments
inferred← citeshttps://doi.org/10.1007/s13042-026-03219-wopenalex-snapshot
Area traffic signal coordination control method based on action value weighted QMIX
inferred← citeshttps://doi.org/10.1007/s13177-022-00305-5openalex-snapshot
Dynamic Weight-based Multi-Objective Reward Architecture for Adaptive Traffic Signal Control System
inferred← citeshttps://doi.org/10.1007/s13177-022-00334-0openalex-snapshot
Reinforcement Learning Based Control Scheme for Emergency Vehicle Preemption with Edge Computing
inferred← citeshttps://doi.org/10.1007/s13177-023-00346-4openalex-snapshot
Deep Reinforcement Q-Learning for Intelligent Traffic Signal Control with Partial Detection
inferred← citeshttps://doi.org/10.1007/s13177-025-00506-8openalex-snapshot
Exploring Urban Traffic Dynamics: Introducing a Benchmark Map for Comprehensive Testing and Evaluation
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Pri-DDQN: learning adaptive traffic signal control strategy through a hybrid agent
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Macroscopic GA-based Multi-Objective Traffic Light Optimization prioritizing tramways
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A survey on deep reinforcement learning approaches for traffic signal control
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An adaptive traffic signal control scheme with Proximal Policy Optimization based on deep reinforcement learning for a single intersection
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111602openalex-snapshot
Store-and-forward with graph attention: Enhanced multi-agent reinforcement learning for emergency-responsive traffic signal control
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Cooperative traffic signal control for a partially observed vehicular network using multi-agent reinforcement learning
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.114904openalex-snapshot
Human-centric traffic signal control for equity: A multi-agent action branching deep reinforcement learning approach
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.116083openalex-snapshot
Text-augmented reinforcement learning for real-time and robust traffic signal control
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.116830openalex-snapshot
Reinforcement learning in urban network traffic signal control: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.120458openalex-snapshot
Traffic signal control using reinforcement learning based on the teacher-student framework
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Fundamental theory of coordination efficiency of signalized intersections on an arterial road
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Deep reinforcement learning for traffic signal control with consistent state and reward design approach
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Robustness enhancement of deep reinforcement learning-based traffic signal control model via structure compression
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GlobalLight: Exploring global influence in multi-agent deep reinforcement learning for large-scale traffic signal control
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IPDALight: Intensity- and phase duration-aware traffic signal control based on Reinforcement Learning
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Network Multi-scale Urban Traffic Control with Mixed Traffic Flow
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Unveiling network capacity potential with imminent supply information part II: Backpressure-based validation
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An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology
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Learning the max pressure control for urban traffic networks considering the phase switching loss
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CVLight: Decentralized learning for adaptive traffic signal control with connected vehicles
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A novel Max Pressure algorithm based on traffic delay
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EMVLight: A multi-agent reinforcement learning framework for an emergency vehicle decentralized routing and traffic signal control system
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Democratizing traffic control in smart cities
inferred← citeshttps://doi.org/10.1016/j.trc.2024.104593openalex-snapshot
HumanLight: Incentivizing ridesharing via human-centric deep reinforcement learning in traffic signal control
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Smoothing-MP: A novel max-pressure signal control considering signal coordination to smooth traffic in urban networks
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A cooperative perception based adaptive signal control under early deployment of connected and automated vehicles
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PASCAL: Pressure Adaptive Signal Control ALgorithm
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Big-data empowered traffic signal control could reduce urban carbon emission
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Adaptive urban traffic signal control based on enhanced deep reinforcement learning
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Traffic signal priority control based on shared experience multi‐agent deep reinforcement learning
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Dynamic traffic signal control using mean field multi‐agent reinforcement learning in large scale road‐networks
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Heterogeneous traffic intersections control design based on reinforcement learning
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A Safe Predictive Control Framework for Traffic Signals With Multi‐Semantic Perception
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Generalized Multi‐Hop Downstream Traffic Pressure for Heterogeneous Perimeter Control
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Ped-MP: A Pedestrian-Friendly Max-Pressure Signal Control Policy for City Networks
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A survey on reinforcement learning-based control for signalized intersections with connected automated vehicles
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A bibliometric analysis and review on reinforcement learning for transportation applications
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Adaptive network traffic control with approximate dynamic programming based on a non-homogeneous Poisson demand model
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Multi-objective traffic signal control considering pedestrian crossings via constraints-decoupled reinforcement learning
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An approximate position-weighted back-pressure traffic signal control policy for traffic networks
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PlanLight: Learning to Optimize Traffic Signal Control With Planning and Iterative Policy Improvement
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Analytically Guided Reinforcement Learning for Green It and Fluent Traffic
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How Well Do Reinforcement Learning Approaches Cope With Disruptions? The Case of Traffic Signal Control
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Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control
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Flexible Traffic Signal Control via Multi-Objective Reinforcement Learning
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Large-Scale Traffic Signal Control Based on Multi-Agent Q-Learning and Pressure
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Modeling and Simulation of Pedestrian Behavior in Traffic Environment: A Systematic Review of Approaches and Software
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Enhancing Game Strategy Optimization Using Deep Reinforcement Learning
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A Spatiotemporal Multi-Agent Framework Based on CoevoMARL for Multi-Intersection Traffic Signal Control
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Training for More Robust and Practical Adaptive Signal Control Models
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Accelerating Distributed Urban Traffic Simulation via Enhanced Stale Synchronous Parallelism
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TSLib: A Unified Traffic Signal Control Framework Using Deep Reinforcement Learning and Benchmarking
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Traffic Signal Control Using Offline Reinforcement Learning
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Graph Attention Network-Based Multi-Agent Reinforcement Learning for Traffic Signal Priority Control
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A Traffic Signal Control Method Based on Improved Deep Reinforcement Learning*
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Towards 6G for Connected Autonomous Vehicles: A Trial Facility Analysis
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Efficient Policy Transfer in Large-Scale Traffic Light Control via Multi-Agent Hierarchical Reinforcement Learning
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OffLight: An Offline Multi-Agent Reinforcement Learning Framework for Traffic Signal Control
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Bidirectional Pressure Enhanced Traffic Signal Control
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The Intersection of Companions: Differential Traffic Signal Control in Multi-Agent Systems
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Toward Efficient Traffic Signal Control: Smaller Network Can Do More
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Adaptive and Responsive Traffic Signal Control Using Reinforcement Learning and Fog Computing
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Challenges Regarding AI Integration in V2X Communication
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RAGTraffic: Utilizing Retrieval-Augmented Generation for Intelligent Traffic Signal Control
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C 2 T: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic–Vehicle Coordination
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FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control
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MOTAR: Intelligent Traffic Signal Control Method Based on Multi-Objective Optimization and Traffic-Aware Representation Learning
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Overview of Extended actor-critic frameworks for multi-intersection Traffic-Signal Control
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Optimizing Traffic Signal Control in Mixed Traffic Scenarios: A Predictive Traffic Information-Based Deep Reinforcement Learning Approach
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Signal Timing Optimization Method Based on Traffic State Representation
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“Less Knowledge is Less” - An Empirical Study of Intelligent Traffic Signal Network Efficiency Under Partial Information
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Multi-Agent Reinforcement Learning for Smart City Automated Traffic Light Control
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Enhancing Decision-Making Strategies in Autonomous Vehicles Under Challenging Conditions
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SoftLight: A Maximum Entropy Deep Reinforcement Learning Approach for Intelligent Traffic Signal Control
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Adaptive Meta-Learning Architectures for Real-Time Decision-Making in Dynamic Environments
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Traffic Signal Control Based on Deep Reinforcement Learning with Simplified State and Reward Definitions
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Probabilistic Graph Neural Networks for Traffic Signal Control
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A Survey on RL-Based Approaches for Traffic Signal and Joint Vehicle-Signal Control
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Multi Agent Deep Reinforcement Learning approach for Traffic Signal Control
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A Traffic Signal Control System Based on TDX Data and Reinforcement Learning
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Enhancing Traffic Signal Control via Lightweight Reward Function Design in Multi-Agent Reinforcement Learning
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DT-MR-FALCON: Digital Twin–Assisted Mixed Reality Emergency Corridor Optimization for Intelligent Ambulance Navigation
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Research on Optimization Algorithm for Multiagent Traffic Signal Cooperative Control Based on Deep Reinforcement Learning
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Vision-Driven Dynamic Traffic Light System for Smart Cities using Edge AI
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A Deep Reinforcement Learning-Based Cooperative Traffic Signal System Through Dual-Sensing Max Pressure Control
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Two-Layer Traffic Signal Optimization: A Edge-assisted Pressure Balance Approach Based on Cooperative Game
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A Dual Large Language Models Architecture with Herald Guided Prompts for Parallel Fine Grained Traffic Signal Control
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Multi-Policy vs. Shared Policy Architectures in Multi-Agent Proximal Policy Optimization for Heterogeneous Traffic Signal Control
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Traffic Signal Control Method Based on UMA-QMIX Algorithm
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EA-A2D3QN: Emergency-Aware Attention-Augmented Dueling Double Deep Q-Network for Adaptive Traffic Signal Control with Emergency Vehicle Prioritization
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TLMOF: An Operating Framework Inspired Hybrid Kernel for Signal Control
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Transit Signal Priority Control with Deep Reinforcement Learning
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Lane-Based Max-Pressure Traffic Signal Control
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Communication-Aware Adaptive Decentralized Traffic Signal Control via Broadcast gate
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SafeCrossLight: Pedestrian-Aware Traffic Light Control using Deep Reinforcement Learning
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A Spatial-Temporal Graph Attention Network for Multi-intersection Traffic Light Control
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Cooperation Skill Motivated Reinforcement Learning for Traffic Signal Control
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Effective Traffic Signal Control with Offline-to-Online Reinforcement Learning
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Deep Reinforcement Learning-Based Intelligent Traffic Signal Controls with Optimized CO2 Emissions
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HeteroLight: A General and Efficient Learning Approach for Heterogeneous Traffic Signal Control
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Applying Neural Monte Carlo Tree Search to Unsignalized Multi-intersection Scheduling for Autonomous Vehicles
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HST-Light: Hierarchical Spatio-Temporal Decoupling for Adaptive Traffic Signal Control
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On Max Pressure Urban Traffic Control with Learning
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Microscopic Model-Based RL Approaches for Traffic Signal Control Generalize Better than Model-Free RL Approaches
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A Collaborative Communication-Qmix Approach for Large-scale Networked Traffic Signal Control
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Designing Reinforcement Learning Agents for Traffic Signal Control with the Right Goals: a Time-Loss based Approach
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Centralized Traffic Signal Control for Multiple Intersections based on Sequence-to-Sequence model and Attention Mechanism
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Mixed Autonomous Supervision in Traffic Signal Control
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Learning Transformer-based Cooperation for Networked Traffic Signal Control
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WaveLearner: A Knowledge-Combined Reinforcement Learning to Understand Coordinated Traffic Signal Control along Urban Arteries
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Meta-Reinforcement Learning for Centralized Multiple Intersections Traffic Signal Control
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A Spatial-Temporal Deep Reinforcement Learning Model for Large-Scale Centralized Traffic Signal Control
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QueueLearner: A Knowledge-Combined Reinforcement Learning to Understand Queuing Evolution in Isolated Traffic Signal Control
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Evaluation of Traffic Signal Control at Varying Demand Levels: A Comparative Study
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Federated Reinforcement Learning for Adaptive Traffic Signal Control: A Case Study in New York City
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PhaseLight: An Universal and Practical Traffic Signal Control Algorithms Based on Reinforcement Learning
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Parallel Learning Based Foundation Model for Networked Traffic Signal Control
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A Case for Monte Carlo Tree Search in Adaptive Traffic Signal Control: Modifiability, Interpretability and Generalization
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Prioritized Phase Split Optimization for Coordinated Traffic Signal Control in Urban Network Using Deep Reinforcement Learning
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eMARLIN+: Overcoming Partial-Observability Caused by Sensor Limitations and Short Detection Ranges in Traffic Signal Control
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SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras
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V2XFormer: A Multi-Stage Transformer for Multi-Agent Reinforcement Learning in V2X-Enabled Traffic Signal Control
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A Subarea-Based Multi Agent Reinforcement Learning Approach for Traffic Signal Control
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HyLight: Hybrid Approach of Reinforcement Learning and Rule-Based Optimization for Coordinated Traffic Signal Control Based on Average Phase Demand
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Cooperative Control for Signals and Vehicles Based on Deep Reinforcement Learning in Mixed Traffic Environments
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A Hierarchical Deep Reinforcement Learning Framework for Traffic Signal Control with Predictable Cycle Planning
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VissimRL: A Multi-Agent Reinforcement Learning Framework for Traffic Signal Control Based on Vissim
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Regional Multi-Agent Cooperative Reinforcement Learning for City-Level Traffic Grid Signal Control
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Urban Traffic Control Meets Decision Recommendation System: A Survey and Perspective
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Ant Colony Optimization With Look-Ahead Mechanism for Dynamic Traffic Signal Control of IoV Systems
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