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Traffic Signal Control
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Control traffic lights/signals to optimize traffic.
<span style="color:grey; opacity: 0.6">( Image credit: Flaticon )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Robustness of Reinforcement Learning-Based Traffic Signal Control under Incidents: A Comparative Study
VLMLight: Traffic Signal Control via Vision-Language Meta-Control and Dual-Branch Reasoning
CV-MP: Max-Pressure Control in Heterogeneously Distributed and Partially Connected Vehicle Environments
Dynamic Location Search for Identifying Maximum Weighted Independent Sets in Complex Networks
Joint Pedestrian and Vehicle Traffic Optimization in Urban Environments using Reinforcement Learning
Safe and Efficient Coexistence of Autonomous Vehicles with Human-Driven Traffic at Signalized Intersections
Federated Hierarchical Reinforcement Learning for Adaptive Traffic Signal Control
A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control
Generalized Phase Pressure Control Enhanced Reinforcement Learning for Traffic Signal Control
Domain Adaptation Framework for Turning Movement Count Estimation with Limited Data
A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
Unicorn: A Universal and Collaborative Reinforcement Learning Approach Towards Generalizable Network-Wide Traffic Signal Control
CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control
Adaptive model predictive control for traffic signal timing with unknown demand and parameters
Large-scale Regional Traffic Signal Control Based on Single-Agent Reinforcement Learning
Enhancing Traffic Signal Control through Model-based Reinforcement Learning and Policy Reuse
Using a single actor to output personalized policy for different intersections
DreamerV3 for Traffic Signal Control: Hyperparameter Tuning and Performance
Toward Dependency Dynamics in Multi-Agent Reinforcement Learning for Traffic Signal Control
Communication Strategy on Macro-and-Micro Traffic State in Cooperative Deep Reinforcement Learning for Regional Traffic Signal Control
FitLight: Federated Imitation Learning for Plug-and-Play Autonomous Traffic Signal Control
FuzzyLight: A Robust Two-Stage Fuzzy Approach for Traffic Signal Control Works in Real Cities
AMM: Adaptive Modularized Reinforcement Model for Multi-city Traffic Signal Control
Integrated Strategy for Urban Traffic Optimization: Prediction, Adaptive Signal Control, and Distributed Communication via Messaging
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning
MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal Control
Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control
Artificial Intelligence in Traffic Systems
Data-Driven Transfer Learning Framework for Estimating Turning Movement Counts
TransferLight: Zero-Shot Traffic Signal Control on any Road-Network
Traffic Co-Simulation Framework Empowered by Infrastructure Camera Sensing and Reinforcement Learning
Intersection-Aware Assessment of EMS Accessibility in NYC: A Data-Driven Approach
A CAV-based perimeter-free regional traffic control strategy utilizing existing parking infrastructure
Integrating Transit Signal Priority into Multi-Agent Reinforcement Learning based Traffic Signal Control
Optimizing Traffic Signal Control using High-Dimensional State Representation and Efficient Deep Reinforcement Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.