RTA-IR: A runtime assurance framework for behavior planning based on imitation learning and responsibility-sensitive safety model-Reference-Cited by-同舟云学术

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RTA-IR: A runtime assurance framework for behavior planning based on imitation learning and responsibility-sensitive safety model

Published:2023-12 Issue: Volume:232 Page:120824
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Peng Yanfei^ORCID,Tan Guozhen,Si Huaiwei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference36 articles.

1. A survey of inverse reinforcement learning: Challenges, methods and progress;Arora;Artificial Intelligence,2021

2. Sandboxing controllers for cyber-physical systems;Bak,2011

3. Multi-agent imitation learning for driving simulation;Bhattacharyya,2018

4. Learning interaction-aware guidance policies for motion planning in dense traffic scenarios;Brito,2021

5. Modern control theory;Brogan,1991

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1. A two-stage framework for parking search behavior prediction through adversarial inverse reinforcement learning and transformer;Expert Systems with Applications;2024-12

2. Reinforcement learning from suboptimal demonstrations based on Reward Relabeling;Expert Systems with Applications;2024-12

3. Guaranteed Safe Satellite Guidance and Navigation Using Reachability Based Switching Controllers;2024 American Control Conference (ACC);2024-07-10

4. Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy;IEEE Open Journal of Intelligent Transportation Systems;2024

5. Research on reinforcement learning based on PPO algorithm for human-machine intervention in autonomous driving;Electronic Research Archive;2024

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