Uninterrupted Maximum Flow on Signalized Traffic Networks
원문 초록
This paper describes a traffic signal control strategy that allows motorists who travel at a recommended speed on suburban arterial two-way roads with a common cycle time to make every traffic signal. A road-to-traveler-feedback-device (RTFD) advises motorists how fast they should travel to do this. Signalized arterial roads where vehicles that travel at the recommended speed make every traffic signal are termed Ride-the-Green-Wave (RGW) roads. Left-turn-arounds enable vehicles to turn left from two-way RGW-roads to intersecting/orthogonal two-way RGW-road while allowing maximum flow at the intersection. The traffic signal control technique that enables vehicles that travel at the recommended speed to make every traffic signal has been verified using a simulation program (RGW-SIM). In addition to introducing novel traffic signal control strategies, the methods presented in this paper have implications for road network design, public transport control, connected and automated vehicles and environmental impacts.
함께 살펴볼 논문
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Joint Pedestrian and Vehicle Traffic Optimization in Urban Environments using Reinforcement Learning
A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control
Generalized Phase Pressure Control Enhanced Reinforcement Learning for Traffic Signal Control
A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control
MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal Control
토론
이 논문과 연결된 포럼 글이 아직 없습니다.