Development of localisation and mapping software for autonomous cars

Autonomous car requires localisation and mapping capabilities to model the surrounding environment and to plan a safe and efficient route for the autonomous driving. Implementation of the localisation and mapping software depends on the type of sensors, map formats, computing environment, and processing algorithms. These dependencies make it difficult to extend, reuse, and maintain localisation and mapping software. The common software platform and software development guideline is a way to address the software dependency issues and to enhance the software reusability, scalability, maintainability, and transferability. Therefore, this study proposes a common software platform and implementation guidelines for localisation and mapping of autonomous cars. The common software platform for localisation and mapping is built on the philosophy of the AUTomotive Open System Architecture (AUTOSAR), which is a standard automotive software platform. The software development methodology of AUTOSAR applies to implementation guidelines of the localisation and mapping software. A graph structure of localisation and mapping is used to design the common software platform. The proposed common software platform and design methodology are evaluated using practical applications of localisation and mapping in a real autonomous car. The results show that the proposed platform and methodology are able to improve the reusability, scalability, maintainability, and transferability of the localisation and mapping software.

• Record URL:
  https://doi.org/10.1049/iet-its.2018.5064
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/1751956X
• Supplemental Notes:
  • Abstract reprinted with permission of the Institution of Engineering and Technology.
• Authors:
  • Jo, Kichun
  • Sunwoo, Myoungho
• Publication Date: 2019-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 406-416
• Serial:
  • IET Intelligent Transport Systems
  • Volume: 13
  • Issue Number: 2
  • Publisher: Institution of Engineering and Technology (IET)
  • ISSN: 1751-956X
  • EISSN: 1751-9578
  • Serial URL: https://ietresearch.onlinelibrary.wiley.com/journal/17519578
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Automobiles; Automotive engineering; Autonomous vehicles; Digital mapping; Mobile robots; Software
• Uncontrolled Terms: Localization
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01710920
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 16 2019 4:32PM