Driver Pattern Study of Las Palmas de Gran Canaria
In our group we have been dealing with traffic simulation for a few years. We plan to develop research initiatives in order to give our microsimulators a higher level of accuracy. We believe that it could help to have a multimodal microsimulation, in the sense of making virtual traffic to be composed not just by one generic vehicle type, but a set of specific types.
Aiming to this target we have performed the research presented in this paper. We have performed a telephone survey, and fieldwork traffic video recordings in order to isolated some driver patterns in the traffic of Las Palmas de Gran Canaria Canary Islands, Spain.
In this paper it is presented the methodology and the early results of the clustering of samples into driver types, based on a small amount of variables. They will be used later in future research to implement multimodal traffic microsimulators. We expect that using the obtained patterns, in the same proportions we have found them, may result in a closer to reality microsimulation.
KeywordsCellular Automaton Intelligent Transportation System Driver Behavior Lane Change Street Type
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- 1.Ericsson, E.: Independent driving pattern factors and their influence on fuel-use and exhaust emission factors. Transportation Research Part D: Transport and Environment 6(5), 325–345 (2001), http://www.sciencedirect.com/science/article/B6VH8-43F8MF3-2/2/52c3be76c9fcb26eb9ad82911a2c72e9 CrossRefGoogle Scholar
- 2.Ericsson, E.: Variability in urban driving patterns. Transportation Research Part D: Transport and Environment 5(5), 337–354 (2000), http://www.sciencedirect.com/science/article/B6VH8-40CJYRS-2/2/33c71bac39659cc9b5c9dfcfbdaa0b42 MathSciNetCrossRefGoogle Scholar
- 3.Lei, Z., Jianqiang, W., Furui, Y., Keqiang, L.: A quantification method of driver characteristics based on driver behavior questionnaire. In: 2009 IEEE Intelligent Vehicles Symposium, pp. 616–620 (June 2009)Google Scholar
- 5.Medina, J.S., Moreno, M.G., Royo, E.R.: Stochastic vs deterministic traffic simulator. Comparative study for its use within a traffic light cycles optimization architecture. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 622–631. Springer, Heidelberg (2005)CrossRefGoogle Scholar
- 6.Sanchez-Medina, J.J., Galan-Moreno, M.J., Rubio-Royo, E.: Study of correlation among several traffic parameters using evolutionary algorithms: Traffic flow, greenhouse emissions and network occupancy. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds.) EUROCAST 2007. LNCS, vol. 4739, pp. 1134–1141. Springer, Heidelberg (2007)CrossRefGoogle Scholar
- 7.Sanchez-Medina, J.J., Galan-Moreno, M.J., Rubio-Royo, E.: Traffic signal optimization in la almozara district in saragossa under congestion conditions, using genetic algorithms, traffic microsimulation, and cluster computing. IEEE Transactions on Intelligent Transportation Systems 11(1), 132–141 (2010)CrossRefGoogle Scholar
- 8.Sanchez-Medina, J.J., Galan-Moreno, M.J., Rubio-Royo, E.: Genetic Algorithms and Cellular Automata: A New Architecture for Traffic Light Cycles Optimization. In: Proceedings of The Congress on Evolutionary Computation 2004 (CEC 2004), vol. 2, pp. 1668–1674 (2004)Google Scholar
- 9.Sanchez-Medina, J.J., Galan-Moreno, M.J., Rubio-Royo, E.: Applying a traffic lights evolutionary optimization technique to a real case: “las ramblas” area in santa cruz de tenerife. IEEE Transactions on Evolutionary Computation (2008)Google Scholar
- 10.Sanchez-Medina, J.J., Galan-Moreno, M.J., de Ugarte, N.A., Rubio-Royo, E.: Simulation times vs. network size in a genetic algorithm based urban traffic optimization architecture. In: Arabnia, H.R., Mun, Y. (eds.) Proceedings of the 2008 International Conference on Genetic and Evolutionary Methods, WORLDCOMP 2008, pp. 255–261. CSREA Press (2008)Google Scholar
- 11.Sneath, P.H.A., Sokal, R.R.: Numerical taxonomy: the principles and practice of numerical classification. Medical Research Council Microbial Systematics Unit, Univ. Leicester, England and Dept. of Ecology and Evolution, State Univ. New York, Stony Brook, NY (1973)Google Scholar
- 12.Tezuka, S., Soma, H., Tanifuji, K.: A study of driver behavior inference model at time of lane change using bayesian networks. In: IEEE International Conference on Industrial Technology, ICIT 2006, pp. 2308–2313 (2006)Google Scholar
- 13.Ulleberg, P.: Personality subtypes of young drivers. relationship to risk-taking preferences, accident involvement, and response to a traffic safety campaign. Transportation Research Part F: Traffic Psychology and Behaviour 4(4), 279–297 (2001), http://www.sciencedirect.com/science/article/B6VN8-44SK486-4/2/4dc9100dce96572fc8fd701f613b5801 CrossRefGoogle Scholar