International Journal of Automotive Technology

, Volume 19, Issue 1, pp 167–177 | Cite as

Belief and fuzzy theories for driving behavior assessment in case of accident scenarios

  • Oussama DerbelEmail author
  • René Jr Landry


The estimation of the overspeed risk before the accident is among the main goals of this paper. The proposed method uses the Energy Equivalent Speed (EES) to assess the severity of an eventual accident. However, the driver behavior evaluation should take into account the parameters related to the Driver, the Vehicle and the Environment (DVE) system. For this purpose, this paper considers a two-level strategy to predict the global risk of an event using the Dempster-Shafer Theory (DST) and the Fuzzy Theory (FT). This paper presents two methods to develop the Expert Model-based Basic Probability Assignment (EM based BPA), which is the most important task in the DST. The first one is based on the accident statistics and the second method deals with the relationship between the Fuzzy and Belief measurements. The experimental data is collected by one driver using our test vehicle and a Micro-intelligent Black Box (Micro-iBB) to collect the driving data. The sensitivity of the developed models is analysed. Our main evaluation concerns the Usage Based Insurance (UBI) applications based on the driving behavior. So, the obtained masses over the defined referential subsets in the DST are used as a score to compute the driver’s insurance premium.


Advanced driver assistance system Driver-vehicle-environment system Fuzzy inference systems Belief theory Driver behavior 


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Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany 2018

Authors and Affiliations

  1. 1.Department of Electric EngineeringUniversity of QuebecMontrealCanada

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