Abstract
“Gap acceptance” behaviour oversees pedestrians crossing manoeuvre at unsignalized road crossings. From a scientific point of view, the study of pedestrians behaviour has a particular interest, since the underlying factors of behavioural interaction between pedestrians and motor vehicles drivers have a strong non-deterministic component, which makes their simulation very complex. In this paper a Fuzzy logic model for representation and simulation of pedestrian behaviour in such a manoeuvre is proposed. The calibration of Fuzzy model membership functions is executed through an Adaptive Neural Network which considers a sample of “gap acceptance” decisions collected on field. The analysis method is at first theoretically defined and then applied to a real pedestrian crossing.
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References
Eurotest, Pedestrian crossings survey in Europe (January 2008), http://www.eurotestmobility.net (Accessed April 30, 2009)
Brilon, W., Koeniga, R., Troutbeck, R.J.: Useful estimation procedures for critical gaps. Transportation Research Part A 33, 161–186 (1999)
Chakroborty, P., Kikuchi, S.: Calibrating the membership functions of the fuzzy inference system: instantiated by car-following data. Transportation Research Part C 11, 91–119 (2003)
Chu, X., Baltes, M.R.: Pedestrian Mid-block Crossing Difficulty National Technical Information Service (NTIS), 5285 Port Royal Road, Springfield, VA 22161, 703-487-465, http://www.nctr.usf.edu (Accessed April 30, 2009)
Palamarthy, S., Mahmassani, H.S., Machemehl, R.B.: Models of Pedestrian Crossing Behavior at Signalized Intersections, Research Report 1296-1, Center for Transportation Research, University of Texas at Austin (1994)
Yang, J., Deng, W., Wang, J., et al.: Modeling pedestrians road crossing behavior in traffic system micro-simulation in China. Transportation Research Part A 40, 280–290 (2006)
Lobjois, R., Cavallo, V.: Age-related differences in street-crossing decisions: The effects of vehicle speed and time constraints on gap selection in an estimation task. Accident Analysis and Prevention 39, 934–943 (2007)
Ottomanelli, M., Iannucci, G.: Modelling pedestrian crossing performances through discrete events based simulation. In: Proceedings of ITS-ILS07, Cracow, Poland (October 2007)
Brewer, M.A., Fitzpatrick, K., Whitacre, J.A., et al.: Exploration of Pedestrian Gap-Acceptance Behavior at Selected Locations, Transportation Research Record. Journal of the Transportation Research Board 1982, 132–140 (2006)
Miller, A.J.: Nine estimators for gap-acceptance parameters. In: Proceedings of the International Symposium on the Theory of Traffic Flow and Transportation, Berkeley, California, June 1971. Elsevier, Amsterdam (1971)
Tian, Z., Vandeheya, M., Robinsona, B.W., et al.: Implementing the maximum likelihood methodology to measure a driver’s critical gap. Transportation Research Part A 33, 187–197 (1999)
Troutbeck, R.J.: Estimating the critical acceptance gap from traffic movements. Physical infrastructure centre, Queensland University of Technology. Research Report 92-5 (1992)
Das, S., Manski, C.F., Manuszak, M.D.: Walk or wait? an empirical analysis of street crossing decisions. Journal of Applied Economy n° 20, 529–548 (2005)
Rossi, R., Meneguzzer, C.: L’uso di osservazioni sperimentali per l’identificazione di modelli fuzzy del comportamento di gap-acceptance. In: Angeli, F. (ed.) Metodi e tecnologie dell’ingegneria dei trasporti. Seminario 2000, pp. 199–213 (2002)
Meneguzzer, C., Rossi, R.: Modelli fuzzy per la simulazione dei comportamenti di Gap Acceptance nelle intersezioni stradali a priorità, Trasporti e Trazione n. 1, 2–11 (2001)
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Ottomanelli, M., Caggiani, L., Iannucci, G., Sassanelli, D. (2010). An Adaptive Neuro-Fuzzy Inference System for Simulation of Pedestrians Behaviour at Unsignalized Roadway Crossings. In: Gao, XZ., Gaspar-Cunha, A., Köppen, M., Schaefer, G., Wang, J. (eds) Soft Computing in Industrial Applications. Advances in Intelligent and Soft Computing, vol 75. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11282-9_27
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DOI: https://doi.org/10.1007/978-3-642-11282-9_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11281-2
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