Automatic Virtual Test Technology for Intelligent Driving Systems Considering Both Coverage and Efficiency

The testing of the intelligent driving systems is faced with the challenges of efficiency because real traffic scenarios are infinite, uncontrollable and difficult to be precisely defined. Based on the complexity index of scenario that designed to measure the test effect indirectly, a new combinational testing algorithm of test cases generation is proposed to make a balance among multiple objects including test coverage, the number of test cases and test effect. Then a joint simulation platform based on Matlab, PreScan and Carsim is built up to realize the construction of 3D test environment, execution of test scenarios and evaluation of test results automatically and seamlessly. The strategy proposed in this paper is validated by applying it to a traffic jam pilot system. The result shows that the proposed strategy can improve the overall complexity of the designed test scenarios effectively, which can help the authors detect system faults faster and easier. And the time required to conduct tests is reduced obviously by means of automation.

• Record URL:
  http://dx.doi.org/10.1109/TVT.2020.3033565
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
• Supplemental Notes:
  • Copyright © 2020, IEEE.
• Authors:
  • Gao, Feng
  • Duan, Jianli
  • Han, Zaidao
  • He, Yingdong
• Publication Date: 2020-12

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 14365-14376
• Serial:
  • IEEE Transactions on Vehicular Technology
  • Volume: 69
  • Issue Number: 12
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 0018-9545
  • Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Driving; Intelligent control systems; Mathematical models; Testing; Three dimensional displays; Traffic congestion
• Identifier Terms: MATLAB (Computer program)
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01766758
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 12 2021 10:06AM