Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic

  • Leonardo GonzálezEmail author
  • Enrique Martí
  • Isidro Calvo
  • Alejandra Ruiz
  • Joshue Pérez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11094)


As vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen.


Automated vehicles Collision avoidance Fuzzy logic Time-to-collision Driving behavior 



This work was supported by the AMASS project (H2020-ECSEL) with grant agreement number 692474.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Leonardo González
    • 1
    • 2
    Email author
  • Enrique Martí
    • 1
  • Isidro Calvo
    • 2
  • Alejandra Ruiz
    • 1
  • Joshue Pérez
    • 1
  1. 1.Tecnalia Research and InnovationDerioSpain
  2. 2.University of the Basque CountryVitoria-GasteizSpain

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