Fuzzy Logic to Evaluate Driving Maneuvers: An Integrated Approach to Improve Training

Husnain Malik; Gregoire S Larue; Andry Rakotonirainy; Frederic Maire

doi:10.1109/TITS.2014.2371061

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Fuzzy Logic to Evaluate Driving Maneuvers: An Integrated Approach to Improve Training

Journal article

Open access

Peer reviewed

Fuzzy Logic to Evaluate Driving Maneuvers: An Integrated Approach to Improve Training

Husnain Malik, Gregoire S Larue, Andry Rakotonirainy and Frederic Maire

IEEE Transactions on Intelligent Transportation Systems, Vol.16(4), pp.1728-1735

2015

DOI: https://doi.org/10.1109/TITS.2014.2371061

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Abstract

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us from building better training programs. Currently, there is a need to develop and evaluate advanced driving assistance systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel intelligent driver training system that analyzes crash risks for a given driving situation, providing avenues for the improvement and personalization of driver training programs. The analysis takes into account numerous variables synchronously acquired from the driver, the vehicle, and the environment. The system then segments out the maneuvers within a drive. This paper further presents the fuzzy set theory to develop the safety inference rules for each maneuver executed during the drive, and presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving maneuvers and then provides a comprehensive analysis of the drive used to give feedback to novice drivers.

Details

Title: Fuzzy Logic to Evaluate Driving Maneuvers: An Integrated Approach to Improve Training
Authors: Husnain Malik (Author) - Queensland University of Technology
Gregoire S Larue (Author) - Queensland University of Technology
Andry Rakotonirainy (Author) - Queensland University of Technology
Frederic Maire (Author) - Queensland University of Technology
Publication details: IEEE Transactions on Intelligent Transportation Systems, Vol.16(4), pp.1728-1735
Publisher: Institute of Electrical and Electronics Engineers
Date published: 2015
DOI: 10.1109/TITS.2014.2371061
ISSN: 1558-0016; 1524-9050
Organisation Unit: Road Safety Research Collaboration; University of the Sunshine Coast, Queensland; School of Law and Society
Language: English
Record Identifier: 99648951002621
Output Type: Journal article

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