Occlusion-Aware Motion Planning With Visibility Maximization via Active Lateral Position Adjustment
Author:
Affiliation:
1. Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan
2. Institute of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan
Funder
New Energy and Industrial Technology Development Organization (NEDO) on Next-Generation AI and Robot Core Technology Development Project
Japan Science and Technology Agency (JST) Project on Open Innovation Platform with Enterprises, Research Institutes and Academia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09784942.pdf?arnumber=9784942
Reference48 articles.
1. Stochastic driver speed control behavior modeling in urban intersections using risk potential-based motion planning framework
2. Extracting Human-Like Driving Behaviors From Expert Driver Data Using Deep Learning
3. Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning
4. POMDPs for Safe Visibility Reasoning in Autonomous Vehicles
5. Predictive Trajectory Planning in Situations with Hidden Road Users Using Partially Observable Markov Decision Processes
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1. Overcoming Fear of the Unknown: Occlusion-Aware Model-Predictive Planning for Automated Vehicles Using Risk Fields;IEEE Transactions on Intelligent Transportation Systems;2024-09
2. Overcoming Blind Spots: Occlusion Considerations for Improved Autonomous Driving Safety;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
3. Highway-Driving with Safe Velocity Bounds on Occluded Traffic;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
4. Bayesian Network-Based Probabilistic Constraints for Safe Autonomous Driving in Occlusion Environments;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24
5. A review of occluded objects detection in real complex scenarios for autonomous driving;Green Energy and Intelligent Transportation;2023-06
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