Kawtar Tikito

Work place: École Nationale Supérieure des Mines de Rabat. Computer Science Department. Rabat, Morocco

E-mail: tikito@enim.ac.ma


Research Interests: Information Systems, Database Management System, Multimedia Information System, Mathematical Analysis


Pr. Kawtar Tikito is a fulltime professor at the MINES-RABAT School, Morocco. She obtained a PhD in computer science from the University Mohammed V of Rabat , Morocco and an engineer degree in computer engineering from Higher National School of Computer Science and Systems Analysis -ENSIAS, Morocco. Her research interests include system analysis, system optimization, information system and supply chain management.

Author Articles
Selecting Qualitative Features of Driver Behavior via Pareto Analysis

By Kawtar Zinebi Nissrine Souissi Kawtar Tikito

DOI: https://doi.org/10.5815/ijmecs.2018.10.01, Pub. Date: 8 Oct. 2018

Driver behavior is the main cause of road crashes; it is the key element that insures a better understanding and improves predictions of car accidents. The main goal of our study is to determine the set of driver behavior features that are the most encountered in literature; we were based on behavioral questionnaires as a source for these features. We selected the questionnaires that are most cited in literature and therefore proved their efficiency through many studies they were employed in. Then we extracted the features considered in their items and classified them by rate of appearance according to the Pareto & ABC principle. In the second part of our study we collaborated with the National Committee for Circulation Accident Prevention (CNPAC) of the Ministry of Transportation of Morocco in order to compare the findings we gathered from literature with the researches they administer. We prepared a questionnaire that contains the final set of features and we transmitted it to experts working in the road safety field to rate it according to their knowledge and experience. Data analysis showed significant differences in some features, which demonstrates the gap between theoretical results and field research.

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