Chang, Kevin Kai-Chun, Liu, Xiangguo, Lin, Chung-Wei, Huang, Chao 
ORCID: 0000-0002-9300-1787 and Zhu, Qi
(2023)
A Safety-Guaranteed Framework for Neural-Network-Based Planners in Connected Vehicles under Communication Disturbance.
In: 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023-4-17 - 2023-4-19.
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Abstract
Neural-network-based (NN-based) planners have been increasingly used to enhance the performance of planning for autonomous vehicles. However, it is often difficult for NN-based planners to balance efficiency and safety in complicated scenarios, especially under real-world communication disturbance. To tackle this challenge, we present a safety-guaranteed framework for NN-based planners in connected vehicle environments with communication disturbance. Given any NN-based planner with no safety-guarantee, the framework generates a robust compound planner embedding the NN-based planner to ensure overall system safety. Moreover, with the aid of an information filter for imperfect communication and an aggressive approach for the estimation of the unsafe set, the compound planner could achieve similar or better efficiency than the given NN-based planner. A comprehensive case study of unprotected left turn and extensive simulations demonstrate the effectiveness of our framework.
| Item Type: | Conference or Workshop Item (Unspecified) |
|---|---|
| Uncontrolled Keywords: | neural-network-based planning, safety guarantee, connected vehicles, communication disturbance |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 14 Aug 2023 07:22 |
| Last Modified: | 15 Mar 2024 17:58 |
| DOI: | 10.23919/date56975.2023.10137184 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3172187 |
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