4.7 Article

Integrity Monitoring of GNSS/INS Based Positioning Systems for Autonomous Vehicles: State-of-the-Art and Open Challenges

Journal

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume 23, Issue 9, Pages 14166-14187

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2022.3149373

Keywords

Navigation; Safety; Monitoring; Global navigation satellite system; Sensors; Autonomous vehicles; Real-time systems; Navigation; connected autonomous vehicle; integrity monitoring

Funding

  1. United Kingdom-Engineering and Physical Sciences Research Council (UK-EPSRC) through the Towards Autonomy: Smart and Connected Control (TASCC) Program [EP/N01300X/1]
  2. L3Pilot Project through the European Union's Horizon 2020 Research and Innovation Program [723051]
  3. University of Warwick's Centre for Doctoral Training in Future Mobility Technologies
  4. Jaguar Land Rover
  5. H2020 Societal Challenges Programme [723051] Funding Source: H2020 Societal Challenges Programme

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This paper provides a comprehensive review of the importance of Integrity Monitoring (IM) for automated driving functions, particularly in positioning and navigation. It introduces various IM methods and systems, and discusses key aspects such as measurement errors and faults related to the data sources. It also identifies the major research challenges in this field.
Positioning and navigation are critical functions of automated driving functions, which help autonomous vehicles determine their absolute and relative positions in the environment that they operate. Integrity Monitoring (IM) systems, which are intended to assess the reliability and trustworthiness of the information provided by the navigation systems, are crucial for ensuring the safety of automated driving functions. This paper provides a comprehensive review of the existing IM frameworks for safety-critical navigation applications and expands on the state-of-the-art of the most recent development of such systems for connected automated vehicles. We mainly focus on IM methods for Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, we also cover IM for map assisted and wireless signal augmented navigation systems, which are promising for high-performance navigation applications, such as automated driving functions. For each main category of solutions, key aspects such as the characteristics of measurement errors and faults related to various data sources are discussed to provide deeper insights into designing of reliable IM systems. Also, some of the major open research challenges to the best knowledge of the authors have been identified and discussed.

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