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A hierarchical fuzzy system for modeling driver’s behavior

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Abstract

The study of human behavior during driving is of primary importance for improving the driver’s security. In this study, we propose a hierarchical driver_vehicle_environment fuzzy system to analyze driver’s behavior under stress conditions on a road. We include climate, road and car conditions in fuzzy modeling. For obtaining fuzzy rules, experts’ opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. The number of fuzzy rules is optimized by Particle Swarm Optimization (PSO) algorithm. Also the frequency of pressing on brake and gas pedals and the number of car’s direction changes are used to determine the driver’s behavior under different conditions. Three different positions are considered for driving and decision making; one position in driving lane and two positions in opposite lane. A fuzzy model called Model 1 is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. The behaviors of different drivers under two stress conditions are investigated. Also we obtained two other models based on fuzzy rules called Model 2 and Model 3 by using Sugeno fuzzy inference. Model 2 has two linguistic terms and Model 3 has four linguistic terms for estimating the time distances with other cars. The results of three models are compared. The comparative studies have shown that simulation results are in good agreement with the real world situations.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Sehraneh Ghaemi, Sohrab Khanmohammadi, Mohammad Ali Tinati & Mohammad Ali Badamchizadeh

Authors
  1. Sehraneh Ghaemi
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  2. Sohrab Khanmohammadi
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  3. Mohammad Ali Tinati
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  4. Mohammad Ali Badamchizadeh
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Corresponding author

Correspondence to Sehraneh Ghaemi.

Additional information

Recommended by Editorial Board member Sungshin Kim under the direction of Editor Young-Hoon Joo.

Sehraneh Ghaemi was born in 1976 in Auromia, Iran. She received her B.S. degrees in power engineering from Amirkabir University of Technology in 2000. She received her M.Sc. and Ph.D. degrees in control engineering from University of Tabriz in 2003 and 2010, respectively. She is now an assistant professor in the Faculty of Electrical and Computer engineering at University of Tabriz. Her research interests include soft computing, genetic algorithm and human behavior modeling.

Sohrab Khanmohammadi received his B.S. degree in industrial engineering from Sharif University, Iran in 1977 and an M.Sc. degree in automatic from University Paul Sabatie, France in 1980 and a Ph.D. degree in automatic from National University, ENSAE, France in 1983. He is now a professor of Electrical Engineering at University of Tabriz. His research interests are fuzzy control, artificial intelligence applications in control and simulation on industrial systems and human behavior.

Mohammad Ali Tinati was born in 1953 in Iran. He received his B.S. degree (with high honor) in 1977, an M.S. degree in 1978 from Northeastern University, Boston, Mass, USA, and a Ph.D. degree from Adelaide University, Australia, in 1999. He had a long affiliation with the University of Tabriz, Iran. He served as an academic member of the Faculty of Electrical Engineering since 1979. His main research interests are biomedical signal processing and speech and image processing.

Mohammad Ali Badamchizadeh was born in Tabriz, Iran, in December 1975. He received his B.S. degree in electrical engineering from University of Tabriz in 1998. He received his M.Sc. and Ph.D. degrees in control engineering from University of Tabriz in 2001 and 2007, respectively. He is now an assistant professor in the Faculty of Electrical and Computer Engineering at University of Tabriz. His research interests include hybrid dynamical systems, stability of systems, adaptive control and intelligent systems.

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Ghaemi, S., Khanmohammadi, S., Tinati, M.A. et al. A hierarchical fuzzy system for modeling driver’s behavior. Int. J. Control Autom. Syst. 10, 517–528 (2012). https://doi.org/10.1007/s12555-012-0308-6

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  • DOI: https://doi.org/10.1007/s12555-012-0308-6

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