Application of MCDA/MCDM methods for an integrated urban public transportation system – case study, city of Cracow

• Autorzy: Kiciński M. , Solecka K.

Identyfikatory

DOI

10.5604/01.3001.0012.2107

• Języki publikacji: EN

Abstrakty

EN

The paper presents the application of the Multiple Criteria Decision Aid/Making (MCDA/MCDM) methodology in the assessment of the development of different scenarios for an urban public transportation system (UPTS). This methodology allows considering several conflicting objectives and performing the evaluation process in a comprehensive manner. This approach also corresponds to the holistic philosophy: different aspects (economic, technical, social etc.) and interest groups – stakeholders (operators, passengers, city government etc.). The MCDA/MCDM methodology is specifically customized to the real life case study – urban public transportation system in the city of Cracow (Poland). A family of 10 criteria is proposed to evaluate several solutions (W) for a UPTS in terms of their usefulness and attractiveness for different stakeholders. These criteria take into account: travel time and standard, effectiveness of the fleet use, environment friendliness, the level of integration and reliability of the UPTS, safety and security, the profitability and availability of the UPTS, investment costs. Considering the possible solutions, the 6 alternatives were designed heuristically and compared with the current state (denotation of alternative W0). Based on the analysis, for the final considerations compared with the current alternative, 7 new solutions of the integrated urban public transportation in Cracow were adopted, denoted as: W1 (bus/rail alternative: integration of high-speed agglomeration rail with bus transportation), W2 (rail/tram/bus alternative: integration of high-speed agglomeration rail with tram and bus transport system), W3 (alternative with the underground: integration of the underground with high-speed agglomeration rail and with tram and bus transport system), W4 (tram/rail alternative: integration of high-speed agglomeration rail with tram transport), W5 (Tram alternative: integration of tram transport with bus transport), W5A (tram alternative: sub-alternative to the alternative W5, integration of tram transport), W6 (dual-mode tram alternative: integration of dual-mode tram transport). The variants of the scenarios for the urban public transportation system were generated by VISUM computer macro-simulation software. The computational experiment was carried out with the practical application of different Multiple Criteria Decision Aid/Making methods: AHP (Expert Choice program) and Electre III (software package Diviz).

Słowa kluczowe

EN

urban transport; public transportation system; transportation integration; transportation planning; transportation simulation; Cracow

PL

transport miejski; system transportu miejskiego; integracja transportu; planowanie transportu; symulacja transportu; Kraków

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2018
• Tom: Vol. 46, iss. 2
• Strony: 71--84
• Opis fizyczny: Bibliogr. 37 poz., rys., tab., wykr.

Twórcy

autor

Kiciński M.

• Poznan University of Technology, Division of Transport System, Poznan, Poland

autor

Solecka K.

• Cracow University of Technology, Faculty of Civil Engineering, Cracow, Poland

Bibliografia

• [1] BASARIC, V., DJORIC, V., JEVDJENIC, A. & JOVIC J., 2015. Efficient Methodology for Assessment of Targets and Policy Measures for Sustainable Mobility Systems. International Journal of Sustainable Transportation, 9(3), 217–226.
• [2] BAUER, M. & SZARATA A., 2013. The methodology of urban transport project evaluation. Prace Naukowe Politechniki Warszawskiej. Transport, (97), 19-29.
• [3] BISCHOFF, J. & MACIEJEWSKI, M., 2016. Simulation of City-wide Replacement of Private Cars with Autonomous Taxis in Berlin. Procedia Computer Science, 83, 237–244.
• [4] BOCAREJO J.P., ESCOBAR D., HERNAN-DEZ, D.O. & GALARZA, D., 2016. Accessibility analysis of the integrated transit system of Bogot. International Journal of Sustainable Transportation, 10(4), 308–320.
• [5] BOJKOVIC N., ANIĆ I. & PEJČIĆ-TARLE S., 2010. One solution for cross-country transport-sustainability evaluation using a modified ELECTRE method. Ecological Economics, 69, 1176–1186.
• [6] BUEHLER, R., PUCHER, J., & ALTSHULER, A, 2017. Vienna's path to sustainable transport. International Journal of Su-stainable Transportation, 11(4), 257–271.
• [7] CEDER, A., 2015. Public Transit Planning and Operation: Modeling, Practice and Behavior. CRC Press.
• [8] DOUMPOS, M., & ZOPOUNIDIS C., 2002. Multicriteria Decision Aid Classification Methods. Dordrecht Kluwer Academic Publishers.
• [9] FIGUEIRA, J., GRECO, S., & EHRGOTT. M., 2005. Multiple criteria decision analysis: State of the art surveys. Boston: Springer Science + Bussines Media.
• [10] HORNI, A., NAGEL, K., & AXHAUSEN K.W., 2016. The Multi-Agent Transport Simulation MATSim London: Ubiquity Press.
• [11] HSU, T.-H., 1999. Public transport system project evaluation using the analytic hierarchy process: a fuzzy Delphi approach. Transportation Planning and Technology, 22(4), 229–246.
• [12] JACQUET-LAGREZE, E., & SISKOS, J., 1982. Assessing a set of additive utility functions for multicriteria decision making, the UTA method. European Journal of Operational Research, 10(2), 151–164.
• [13] JEON, C. M., AMEKUDZI, A. A., and GUENSLER, R.L., 2010. Evaluating Plan Alternatives for Transportation System Sustainability: Atlanta Metropolitan Region. International Journal of Sustainable Transportation, 4(4), 227–247.
• [14] KAROŃ, G., JANECKI, R., & SOBOTA, A., 2010, Traffic modeling in Silesian Area – public transport network model. Scientific Journal of Silesian University of Technology. Series Transport, 66, 35-42.
• [15] KICIŃSKI, M., JUDT, W., & K｣OSOWIAK, R., 2017. Multicriterial evaluation of variants arrival of the inhabitants from Poznan agglomeration to the Poznan. Autobusy. Technika, Eksploatatcja, Systemy Transportowe, 12, 560–563.
• [16] MARDANI, A., JUSOH, A., MD NOR, K., KHALIFAH, Z., ZAKWAN, N., &A. VALI-POUR, A., 2015., Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istražvanja, 28(1), 516–571.
• [17] MARDANI, A., ZAVADSKAS, E. K., JUSOH A., & MD. NOR, K., 2016. Multiple criteria de-cision-making techniques in transportation sys-tems: a systematic review of the state of the art literature. Transport, 31(3), 359–385.
• [18] MARTÍNEZ, L. M., CORREIA, G. H. DE A., MOURA, F., & MENDES LOPES, M., 2017. Insights into carsharing demand dynamics: Outputs of an agent-based model application to Lisbon, Portugal. International Journal of Su-stainable Transportation, 11(2), 148–159.
• [19] MERKISZ-GURANOWSKA, A., & STAŃKO, K., 2015. Creating a Sustainable Urban Transport – the Ecological Aspect. Logistics and Transport, 2(26), 83–92.
• [20] PEREZ J. ,C., CARRILLO, M., H., & MON-TOYA-TORRES, J.R., 2015. Multicriteria approaches for urban passenger transport systems: a literature review. Annals of Operations Research, 226(1), 69– 87.
• [21] ROY, B., 1968. Classement et choix en preference de points de vue multiples: La method ELECTRE. Revue Francaise D’informatique et de Recherche Operationnelle, 2(8), pp.57–75.
• [22] ROY, B., 1990. Multiple-criteria decision aid-ing methods. Scientific and Technical Publishing, Warsaw.
• [23] ROY, B., 1996. Multicriteria Methodology for Decision Analysis. Kluwer Academic Publishers.
• [24] SAATY, T. 1980. The Analytic hierarchy pro-cess: Planning, priority setting, resource allocation. USA: McGraw-Hill.
• [25] SAATY, T., 1990. How to make a decision: The analytic process. European Journal of Operational Research, 48, 9–26.
• [26] SAATY, T., 1995. Transport planning with multiple criteria: The Analytic hierarchy process. Applications and progress review. Journal of Advanced Transportation, 29(1), 81–126.
• [27] SALAVATI, A., HAGHSHENAS, H., GHADIRIFARAZ, B., LAGHAEI, J., & EFTEKHARI, G., 2016. Applying AHP and Clustering Approaches for Public Transportation Decision making: A Case Study of Isfahan City. Journal of Public Transportation, 19(4), 38–55.
• [28] SATTY, T., 1999. Fundamentals of the analytic network process. Proceedings of ISAHP, 1/14, Japan: Kobe.
• [29] SAWICKI, P., KICIŃSKI, M., & FIEREK, S., 2016. Selection of the most adequate trip-modelling tool for integrated transport planning system. Archives of Transport, 37(1), 55–66.
• [30] SCHMIDT, M. E., 2014. Integrating Routing Decisions in Public Transportation Problems. New York: Springer-Verlag.
• [31] SOLECKA, K., 2013. Multiple-criteria rating of the alternatives of the integrated urban public transport system. PhD dissertation. Cracow University of Technology, Cracow.
• [32] SZARATA, A., 2014. Simulation modeling of passenger flows as a key for planning of subway's construction. Budownictwo Górnicze i Tunelowe, 2, 48–53.
• [33] VAIDYA, O.S., 2014. Evaluating the Performance of Public Urban Transportation Systems in India. Journal of Public Transportation, 20(2), 174-191.
• [34] VERMA A., & RAMANAYYA, T.V., 2014. Public Transport Planning and Management in Developing Countries. CRC Press Taylor & Francis Group.
• [35] VINCKE, P., 1992. Multicriteria decision-aid. John Wiley & Sons, Chichester.
• [36] VUCHIC, V., 2007. Urban transit systems and technology. John Wiley & Sons, Hoboken.
• [37] ZEGRAS, C. & RAYLE, L., 2012. Testing the rhetoric: An approach to assess scenario planning's role as a catalyst for urban policy integration. Futures, 44(4), 303–318.