Integrated Behavior Planning and Motion Control for Autonomous Vehicles with Traffic Rules Compliance
Author:
Affiliation:
1. The Hong Kong University of Science and Technology (Guangzhou),Robotics and Autonomous Systems Thrust,Guangzhou,China
2. The Hong Kong University of Science and Technology,Department of Mechanical and Aerospace Engineering,Hong Kong SAR, China
Funder
Department of Education of Guangdong Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10354348/10354529/10354858.pdf?arnumber=10354858
Reference21 articles.
1. Hierarchical Motion Planning for Autonomous Vehicles in Unstructured Dynamic Environments
2. Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
3. Cooperative Collision Avoidance for Overtaking Maneuvers in Cellular V2X-Based Autonomous Driving
4. An Enabling Trajectory Planning Scheme for Lane Change Collision Avoidance on Highways
5. Model-free Deep Reinforcement Learning for Urban Autonomous Driving
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1. Multi-Step Continuous Decision Making and Planning in Uncertain Dynamic Scenarios Through Parallel Spatio-Temporal Trajectory Searching;IEEE Robotics and Automation Letters;2024-10
2. Incremental Learning-Based Real-Time Trajectory Prediction for Autonomous Driving via Sparse Gaussian Process Regression;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
3. Evaluation and Optimization of Adaptive Cruise Control in Autonomous Vehicles using the CARLA Simulator: A Study on Performance under Wet and Dry Weather Conditions;2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2024-04-27
4. Continuous Decision-Making in Lane Changing and Overtaking Maneuvers for Unmanned Vehicles: A Risk-Aware Reinforcement Learning Approach With Task Decomposition;IEEE Transactions on Intelligent Vehicles;2024-04
5. Motion Planning for Autonomous Vehicles in Unanticipated Obstacle Scenarios at Intersections Based on Artificial Potential Field;Applied Sciences;2024-02-17
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