Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (10): 1588-1597.doi: 10.23940/ijpe.20.10.p10.15881597

Previous Articles     Next Articles

A Survey of the Inadequacies in Traffic Sign Recognition Systems for Autonomous Vehicles

Angelica F. Magnussena, Nathan Leb, Linghuan Huc, and W. Eric Wongc,*   

  1. aCollege of Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA;
    bCollege of Science and Engineering, Texas A&M University, Corpus Christi, TX, 78412, USA;
    cComputer Science Department, University of Texas at Dallas, Richardson, TX, 75080, USA
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address: ewong@utdallas.edu
  • About author:Angelica F. Magnussen is a B.S. student in computer science at the University of Texas at Arlington. Her research interests include software engineering, software testing, artificial intelligence, and distributed systems. Contact her at angelica.magnussen@mavs.uta.edu.
    Nathan Le is a B.S. student in Computer Science at Texas A&M University Corpus Christi. His research interests include artificial intelligence and autonomous vehicles. Contact him at nle10@islander.tamucc.edu.
    Linghuan Hu is a Ph.D. student in software engineering at the University of Texas at Dallas. His research interests include combinatorial testing and test generation. Hu received a M.S. in software engineering from the University of Texas at Dallas. Contact him at linghuan.hu@utdallas.edu.
    W. Eric Wong is a professor and the director of the Advanced Research Center for Software Testing and Quality Assurance in Computer Science at the University of Texas at Dallas. His research focuses on helping practitioners improve the quality of software while reducing the cost of production.
    Wong received a Ph.D. in computer science from Purdue University, West Lafayette, Indiana. He is the Editor-in-chief of IEEE Transactions on Reliability and the corresponding author for this article. Contact him at ewong@utdallas.edu.

Abstract: Traffic sign recognition systems are crucial for autonomous vehicles. They assist autonomous driving systems by collecting road-related information, such as speed limits, stop signs, etc., that are necessary for safe driving. However, as evidenced by recent autonomous vehicle crashes and recognition system failure-related studies, there are serious concerns about the inadequacies of the traffic sign recognition systems and their used techniques. In response to the industrial needs and to help practitioners improve the reliability and safety of the traffic sign recognition systems, this paper discusses the general architectural outline of traffic sign recognition systems and the challenges that must be overcome, in order for traffic sign recognition systems to be safe and reliable. An in-depth discussion of various solutions is given to provide practitioners valuable insight into the improvement of traffic sign recognition systems.

Key words: autonomous vehicles, traffic sign recognition system, software safety