FP-WDDQN: An improved deep reinforcement learning algorithm for adaptive traffic signal control
Author:
Affiliation:
1. Nanjing University of Posts and Telecommunications,Jiangsu Key Laboratory of Big Data Security & Intelligent Processing,Nanjing,China
2. Nanjing University of Posts and Telecommunications,School of Computer Science,Nanjing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10411504/10411508/10411634.pdf?arnumber=10411634
Reference30 articles.
1. Comparison of delay estimates at under-saturated and over-saturated pre-timed signalized intersections
2. Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks
3. ADONiS—Adaptive Online Nonsingleton Fuzzy Logic Systems
4. An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator
5. Traffic signal timing optimisation based on genetic algorithm approach, including drivers’ routing
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