A Combined Fuzzy Logic and Analytical Hierarchy Process Method for Optimal Selection and Locating of Pedestrian Crosswalks
الموضوعات :
Mohammad Reza Ahadi
1
(Associate Professor,Transportation Research Institute, Road, Housing and Development Research Center(BHRC),Tehran, Iran)
Ali Reza Mahpour
2
(Assistant Professor, Transportation Research Institute, Road, Housing and Development Research Center(BHRC), Tehran, Iran)
Vahid Taraghi
3
(M.Sc. Transportation Engineering, K.N.Toosi University of Technology, Tehran, Iran)
الکلمات المفتاحية: fuzzy logic, analytical hierarchy process, safety, ArcGIS, Pedestrian crosswalk,
ملخص المقالة :
One of the main challenges for transportation engineers is the consideration of pedestrian safety as the most vulnerable aspect of the transport system. In many countries around the world, a large number of accidents recorded by the police are composed of accidents involving pedestrians and vehicles, for example when pedestrians may be struck by passing vehicles when crossing the street. Careful consideration of the parameters that are involved in selecting the type and optimum location of pedestrian crosswalks results in a higher pedestrian safety coefficient and a reduced accident rate at these facilities. At the start of this study, these parameters that are important in specifying the optimum type and location of pedestrian crosswalks were determined. Then the data layers of these identified parameters were defined using the ArcGIS software. These layers can subsequently be used for determination of the optimal positioning of pedestrian crosswalks. To specify the boundary changes for each parameter, fuzzy membership functions were defined for each parameter using fuzzy logic. The Analytical Hierarchy Process method (AHP) was used in order to combine these layers of information after the fuzzy membership functions were defined. Expert Choice software was used to determine the final weight resultant of the professionals' poll that was conducted. A field study sample has been carried out to determine the optimal location of pedestrian crosswalks in the city of Tehran. The final output from the ArcGIS software shows the ideal locations and the appropriate type of pedestrian crosswalks in the field study sample. The results indicate that the use of fuzzy logic in definition of membership functions of location parameters, along with using AHP for determination of the weight of data layers built in ArcGIS, is a satisfactory combined method for specifying the location of pedestrian crosswalks.
AASHTO, A. (2001). Policy on geometric design of highways and streets. American Association of State Highway and Transportation Officials, Washington, DC, 1(990), 158.
Agenda, T. (2017). Manual on Uniform Traffic Control Devices. Transportation.
Anciaes, P. R., & Jones, P. (2016, January). Estimating preferences for pedestrian crossing facilities. In Universities' Transport Study Group 48th Annual Conference Proceedings (Vol. 2016). Universities' Transport Study Group.
Crandall, J. R., Bhalla, K. S., & Madeley, N. J. (2002). Designing road vehicles for pedestrian protection. BMJ: British Medical Journal, 324(7346), 1145.
Kasemsuppakorn, P., & Karimi, H. A. (2013). A pedestrian network construction algorithm based on multiple GPS traces. Transportation research part C: emerging technologies, 26, 285-300.
Knoblauch, R. L., Nitzburg, M., & Seifert, R. F. (2001). Pedestrian Crosswalk Case Studies: Sacramento, California; Richmond, Virginia; Buffalo, New York; Stillwater, Minnesota (No. FHWA-RD-00-103,).
Lalani, N. (2001). Alternative treatments for at-grade pedestrian crossings. Institute of Transportation Engineers. ITE Journal, 71(9), 36.
Lam, W. H., & KS, C. (2005). Multi-modal network design: Selection of pedestrianisation location. Journal of the Eastern Asia Society for Transportation Studies, 6, 2275-2290.
Lamm, R., Psarianos, B., & Mailaender, T. (1999). Highway design and traffic safety engineering handbook.
Lassarre, S., Bonnet, E., Bodin, F., Papadimitriou, E., Yannis, G., & Golias, J. (2012). A GIS-based methodology for identifying pedestrians’ crossing patterns. Computers, Environment and Urban Systems, 36(4), 321-330.
Manual, H. C. (2010). Highway capacity manual. Washington, DC.
NZ Transport Agency, (2005). Maricopa Association of Governments, Pedestrian policies and design guideline, City of Boulder Transportation Division.
Papadimitriou, E., Lassarre, S., & Yannis, G. (2016, a). Introducing human factors in pedestrian crossing behaviour models. Transportation research part F: traffic psychology and behaviour, 36, 69-82.
Papadimitriou, E., Lassarre, S., & Yannis, G. (2016, b). Pedestrian risk taking while road crossing: a comparison of observed and declared behaviour. Transportation Research Procedia, 14, 4354-4363.
Pedestrian accident Data of Shariati Street, (2008), Traffic Department of Tehran.
Pedestrian design considerations, (2009). Washington State Department of Transportation, Technical Report, Warwickshire County Council.
Policy for the provision of pedestrian crossings and pedestrian phases at traffic signals, (2005). Planning, Transport and Economic Strategy, Warwickshire County Council.
Quistberg, D. A., Howard, E. J., Hurvitz, P. M., Moudon, A. V., Ebel, B. E., Rivara, F. P., & Saelens, B. E. (2017). The Relationship Between Objectively Measured Walking and Risk of Pedestrian–Motor Vehicle Collision. American journal of epidemiology, 185(9), 810-821.
Sohrabpour, M., Mirzaee, H., Rostami, S., & Athari, M. (1999). Elemental concentration of the suspended particulate matter in the air of Tehran. Environment international, 25(1), 75-81.
Tehran Transportation Master Plan, (2007). Tehran Comprehensive Transportation and Traffic Studies Co., Tehran Transportation and Traffic at a Glance Report.
Travel, E. N. (2006). Federal highway administration university course on bicycle and pedestrian transportation.
Tui, R. N. S. (1980). Analytical Hierarchy Process.
Zimmermann, H. J. (2011). Fuzzy set theory—and its applications. Springer Science & Business Media.
