Managing Risk in the Design of Modular Systems for an Autonomous Shuttle
This paper presents an analysis and implementation of a robust autonomous driving system for an electric passenger shuttle in shared spaces. The authors present results of a risk assessment for their vehicle scenario and develop a flexible architecture that integrates safety features and optimises open-source software, facilitating research and operational functionality. Identifying limitations of the Robot Operating System (ROS) framework, the incorporate their own control measures for autonomous, unsupervised operation with enhanced intelligence. The study emphasizes algorithm selection based on application requirements to ensure optimal performance. They discuss system improvements, including monitoring node implementation and localization algorithm selection. Future work should explore transitioning to a real-time operating system (RTOS) and establishing standardized software engineering practices for consistent reliability. Their findings contribute to effective autonomous shuttle systems in shared spaces, promoting safer and more reliable transportation solutions.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/26877813
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Supplemental Notes:
- © 2024 The Authors.
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Authors:
- Drage, Thomas H
- Quirke-Brown, Kieran
- Haddad, Lemar
- Lai, Zhihui
- Lim, Kai Li
- Bräunl, Thomas
- Publication Date: 2024
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 555-565
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Serial:
- IEEE Open Journal of Intelligent Transportation Systems
- Volume: 5
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 2687-7813
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Active safety systems; Advanced vehicle control systems; Autonomous vehicles; Risk management; Shuttle buses
- Subject Areas: Design; Highways; Public Transportation; Vehicles and Equipment;
Filing Info
- Accession Number: 01941670
- Record Type: Publication
- Files: TRIS
- Created Date: Dec 31 2024 4:31PM