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Multi-Task Lane-Free Driving Strategy for Connected and Automated Vehicles: A Multi-Agent Deep Reinforcement Learning Approach

https://doi.org/10.2139/ssrn.4798023
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Giving commands to a self-driving car: How to deal with uncertain situations?
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Multi-agent based scheduling method for tandem automated guided vehicle systems
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Driving Strategy for Vehicles in Lane-Free Traffic Environment Based on Deep Deterministic Policy Gradient and Artificial Forces
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Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving
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Space-weighted information fusion using deep reinforcement learning: The context of tactical control of lane-changing autonomous vehicles and connectivity range assessment
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Cooperative path and trajectory planning for autonomous vehicles on roads without lanes: A laboratory experimental demonstration
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Outracing champion Gran Turismo drivers with deep reinforcement learning
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Deep Q‐network implementation for simulated autonomous vehicle control
inferredcites →https://doi.org/10.1080/15472450.2017.1336053openalex-extracted
Connected and automated vehicle systems: Introduction and overview
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On the Theory of the Brownian Motion
inferredcites →https://doi.org/10.1109/access.2020.3022755openalex-extracted
Decision-Making Strategy on Highway for Autonomous Vehicles Using Deep Reinforcement Learning
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A Comprehensive Survey on Vehicular Networking: Communications, Applications, Challenges, and Upcoming Research Directions
inferredcites →https://doi.org/10.1109/icra40945.2020.9197132openalex-extracted
Driving in Dense Traffic with Model-Free Reinforcement Learning
inferredcites →https://doi.org/10.1109/itsc.2018.8569448openalex-extracted
High-level Decision Making for Safe and Reasonable Autonomous Lane Changing using Reinforcement Learning
inferredcites →https://doi.org/10.1109/itsc.2018.8569568openalex-extracted
Automated Speed and Lane Change Decision Making using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/itsc.2018.8569938openalex-extracted
Microscopic Traffic Simulation using SUMO
inferredcites →https://doi.org/10.1109/itsc48978.2021.9564698openalex-extracted
Optimal Path Planning for Connected and Automated Vehicles in Lane-free Traffic
inferredcites →https://doi.org/10.1109/itsc55140.2022.9921864openalex-extracted
Empirical Investigation of Properties of Lane-free Automated Vehicle Traffic
inferredcites →https://doi.org/10.1109/itsc55140.2022.9922205openalex-extracted
An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobility
inferredcites →https://doi.org/10.1109/itsc55140.2022.9922249openalex-extracted
Automated vehicle driving on large lane-free roundabouts
inferredcites →https://doi.org/10.1109/itsc55140.2022.9922282openalex-extracted
Lane-Free Traffic: History and State of the Art
inferredcites →https://doi.org/10.1109/itsc57777.2023.10421795openalex-extracted
A Novel Potential Line Strategy for Autonomous Vehicle Control in Lane-Free Traffic
inferredcites →https://doi.org/10.1109/ivs.2018.8500630openalex-extracted
Human-like Autonomous Vehicle Speed Control by Deep Reinforcement Learning with Double Q-Learning
inferredcites →https://doi.org/10.1109/jproc.2020.3042681openalex-extracted
Lane-Free Artificial-Fluid Concept for Vehicular Traffic
inferredcites →https://doi.org/10.1109/mt-its56129.2023.10241608openalex-extracted
Integrated Intersection Control for Lane-Free Connected and Automated Driving
inferredcites →https://doi.org/10.1109/tits.2020.3047129openalex-extracted
Harmonious Lane Changing via Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/tits.2021.3054625openalex-extracted
Deep Reinforcement Learning for Autonomous Driving: A Survey
inferredcites →https://doi.org/10.1109/tits.2022.3229518openalex-extracted
Robust Decision Making for Autonomous Vehicles at Highway On-Ramps: A Constrained Adversarial Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/tiv.2023.3241200openalex-extracted
Optimal Trajectory Planning for Connected and Automated Vehicles in Lane-Free Traffic With Vehicle Nudging
inferredcites →https://doi.org/10.1109/tnnls.2020.3042981openalex-extracted
Adaptive Decision-Making for Automated Vehicles Under Roundabout Scenarios Using Optimization Embedded Reinforcement Learning
inferredcites →https://doi.org/10.1109/tvt.2021.3049794openalex-extracted
Decision-Making and Planning Method for Autonomous Vehicles Based on Motivation and Risk Assessment
inferredcites →https://doi.org/10.1109/tvt.2022.3207054openalex-extracted
Optimal Lane-Free Crossing of CAVs Through Intersections
inferredcites →https://doi.org/10.1111/mice.12495openalex-extracted
A deep learning algorithm for simulating autonomous driving considering prior knowledge and temporal information
inferredcites →https://doi.org/10.1111/mice.12702openalex-extracted
Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles
inferredcites →https://doi.org/10.1126/scirobotics.aaw1975openalex-extracted
Neural network vehicle models for high-performance automated driving
inferredcites →https://doi.org/10.1145/1400713.1400740openalex-extracted
TraCI
inferredcites →https://doi.org/10.1146/annurev-control-060117-105157openalex-extracted
Planning and Decision-Making for Autonomous Vehicles
inferredcites →https://doi.org/10.1177/03611981231159405openalex-extracted
Modeling Vehicle Flocking in Lane-Free Automated Traffic
inferredcites →https://doi.org/10.1631/fitee.1900533openalex-extracted
Deep reinforcement learning: a survey
inferredcites →https://doi.org/10.2352/issn.2470-1173.2017.19.avm-023openalex-extracted
Deep Reinforcement Learning framework for Autonomous Driving
inferredcites →https://doi.org/10.3141/2623-01openalex-extracted
Realistic Car-Following Models for Microscopic Simulation of Adaptive and Cooperative Adaptive Cruise Control Vehicles
inferredcites →https://doi.org/10.3390/futuretransp2040057openalex-extracted
Multi-Task Vehicle Platoon Control: A Deep Deterministic Policy Gradient Approach
inferredcites →https://doi.org/10.3390/systems11030134openalex-extracted
Deep Reinforcement Learning Reward Function Design for Autonomous Driving in Lane-Free Traffic
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1509.02971openalex-extracted
Continuous control with deep reinforcement learning
inferredcites →https://doi.org/10.48550/arxiv.1611.01491openalex-extracted
Understanding Deep Neural Networks with Rectified Linear Units
inferredcites →https://doi.org/10.48550/arxiv.1706.02275openalex-extracted
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
inferredcites →https://doi.org/10.48550/arxiv.1912.01703openalex-extracted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
inferredcites →https://doi.org/10.65109/zhif5176openalex-extracted
Collaborative Multiagent Decision Making for Lane-Free Autonomous Driving
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