Multiagent Reinforcement Learning-Based Signal Planning for Resisting Congestion Attack in Green Transportation

Keyphrases

• Learning-based 100%
• Green Transportation 100%
• Multi-intersection 100%
• Congestion Attack 100%
• Multi-agent Reinforcement Learning 100%
• Connected Vehicles 75%
• Vehicle-based 50%
• Traffic Network 50%
• Total Delay 50%
• Exhaust Emissions 25%
• Fuel Consumption 25%
• Consumption Emissions 25%
• Energy Efficiency 25%
• CO2 Emissions 25%
• Traffic Congestion 25%
• Signal Control 25%
• Transportation System 25%
• Total CO2 25%
• Wireless Communication 25%
• Signalized Intersection 25%
• Connected Vehicle Technology 25%
• Transportation Efficiency 25%
• Reinforcement Learning Problems 25%
• Actor-attention-critic 25%
• Signal Control System 25%
• Transportation Infrastructure 25%
• Traffic Management System 25%
• Collaborative Planning 25%
• Planning Problem 25%
• Traffic Efficiency 25%
• Traffic Correlation 25%
• Experiment Results 25%
• Low Traffic 25%
• Planning Algorithms 25%
• U.S. Department Of Transportation (USDOT) 25%
• Transportation Energy 25%
• Collaborative Signals 25%

Computer Science

• Control Signal 100%
• Reinforcement Learning 100%
• Traffic Network 100%
• multi-agent 100%
• Energy Efficiency 50%
• Learning Problem 50%
• Wireless Communication 50%
• Multi-Agent Reinforcement Learning 50%
• Traffic Control System 50%
• Planning Algorithm 50%

Engineering

• Reinforcement Learning 100%
• Multiagents 100%
• Environmentally Sustainable Transport 100%
• Control System 66%
• Exhaust Emission 33%
• Infrastructure 33%
• Energy Conservation 33%
• Energy Efficiency 33%
• Wireless Communication 33%
• Traffic Control 33%
• Control Signal 33%