Fault Detection, Isolation, Identification and Recovery (FDIIR) Methods for Automotive Perception Sensors Including a Detailed Literature Survey for Lidar

Thomas Gölles*, Birgit Schlager, Stefan Muckenhuber

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


Perception sensors such as camera, radar, and lidar have gained considerable popularity in the automotive industry in recent years. In order to reach the next step towards automated driving it is necessary to implement fault diagnosis systems together with suitable mitigation solutions in automotive perception sensors. This is a crucial prerequisite, since the quality of an automated driving function strongly depends on the reliability of the perception data, especially under adverse conditions. This publication presents a systematic review on faults and suitable detection and recovery methods for automotive perception sensors and suggests a corresponding classification schema. A systematic literature analysis has been performed with focus on lidar in order to review the state-of-the-art and identify promising research opportunities. Faults related to adverse weather conditions have been studied the most, but often without providing suitable recovery methods. Issues related to sensor attachment and mechanical damage of the sensor cover were studied very little and provide opportunities for future research. Algorithms, which use the data stream of a single sensor, proofed to be a viable solution for both fault detection and recovery.
Original languageEnglish
Article number3662
Pages (from-to)1-21
Number of pages21
Issue number13
Publication statusPublished - 30 Jun 2020


  • Automotive
  • Fault detection
  • Fault detection and isolation (FDIR)
  • Fault diagnosis
  • Fault identification
  • Fault isolation
  • Fault recovery
  • Lidar
  • Perception sensor

ASJC Scopus subject areas

  • Analytical Chemistry
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering
  • Biochemistry

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