Analysis of the pedestrian traffic in transport nodes in Radom
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Published:
Jan 19, 2020
Keywords:
pedestrian, pedestrian trips, public transport, transport nodes, transport behaviours, destination of pedestrian journeys
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Abstract
The efficient functioning of the transport system in each area requires that account be taken of the fact that each journey consists of a chain of elementary movements on foot or by means of transport. The construction of an effective public transport system is one of the methods to reduce traffic congestion, especially in city centres. The inter-change synchronization is the way to increase the efficiency of public transport.
The purpose of the paper is to present the results of research on the intensity of pedestrian traffic at interchanges as a function of time in the city of Radom. Pedestrian movements play an important role not only in the vicinity of transport nodes. Their production and quality also determine the assessment of these movements as one of the stages of production of combined movements. The tendency to pedestrian travel (or lack of it) also affects public and individual transport journeys. Based on the survey conducted in households, the structure of movement (size and motivations) of the inhabitants of Radom is given.
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How to Cite
Dębowska-Mróz, M. ., Ferensztajn-Galardos, E. ., Krajewska, R. ., & Rogowski, A. . (2020). Analysis of the pedestrian traffic in transport nodes in Radom. Journal of Management and Financial Sciences, (39), 71–94. https://doi.org/10.33119/JMFS.2019.39.6
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References
Legal documents:
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3. Cascetta, E., Papola, A., Marzano, V., Simonelli, F., Vitiello, I. (2013). Quasi-dynamic estimation of o-d flows from traffic counts: Formulation, statistical validation and performance analysis on real data. Transportation Research, Part B 55, pp. 171-187.
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10. Dębowska-Mróz, M., Zawisza, T. (2017). Ocena napełnienia samochodów osobowych w aspekcie poprawy wykorzystania przestrzeni transportowej w miastach. Autobusy, No. 12, pp. 1814-1818.
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13. Kieu, L.M., Bhaskar, A., Cools, M., Chung, E. (2017). An investigation of timed transfer coordination using event based multi agent simulation. Transportation Research, Part C 81, pp. 363-378.
14. Liu, T., Ceder, A. (2017). Integrated Public Transport Timetable Synchronization and Vehicle Scheduling with Demand Assignment: A Bi-objective Bi-level Model Using Deficit Function Approach. Transportation Research Procedia, No. 23, pp. 341-361.
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19. Numov, V., Samchuk, G. (2017). Class Library for Simulations of Passenger Transfer Nodes as Elements of the Public Transport System. Procedia Engineering, No. 187, pp. 77-81.
20. Omar, J. Ibarra-Rojas, O.J., Yasmin, A. Rios-Solis, Y.A. (2012). Synchronization of bus time- tabling. Transportation Research, Part B 46, pp. 599-614.
21. Oziomek, J., Rogowski, A. (2018). Improvement of Regularity of Urban Public Transport Lines by Means of Intervals Synchronization. Transport Problems, Vol. 13, Iss. 4, pp. 91-102, DOI: 10.20858/tp.2018.13.4.9.
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23. Rahman, K., Ghani, N.A., Kamil, A.A., Mustafa, A., Chowdhury, A.K. (2013). Modelling Pedestrian Travel Time and the Design of Facilities: A Queuing Approach. PLOS-ONE, Vol. 8, Iss. 5, May, pp. 1-13. www.plosone.org.
24. Schobel, A. (2012). Line planning in public transportation: models and methods. OR Spectrum, No. 34, pp. 491-510, DOI 10.1007/s00291-011-0251-6.
25. Schobel, A. (2017). An eigenmodel for iterative line planning, timetabling and vehicle scheduling in public transportation. Transportation Research, Part C 74, pp. 348-365.
26. Serge, P., Hoogendoorn, S.P., Bovy, P.H.L. (2005). Pedestrian Travel Behavior Modeling. Networks and Spatial Economics, No. 5, pp. 193-216.
27. Sierpiński, G., Staniek, M., Celiński, I., Czech, P., Barcik, J. (2015). Identification of pedestrian travel in modeling of modal split and transport accessibility. Logistyka, No. 4, pp. 1495-1502.
28. Varga, B., Tettamanti, T., Kulcsar, B. (2018). Optimally combined headway and timetable reli- able public transport system. Transportation Research, Part C 92, pp. 1-26.
29. Wachowiak, W. (2018). Integracja podsystemów transportowych w węzłach przesiadkowych komunikacji publicznej Poznania w oparciu o kolejowe dworce miejskie. Biuletyn KPZK PAN, Vol. 270, pp. 82-106.
30. Wu, Y., Tang, J., Yu, Y., Pan, Z. (2015). A stochastic optimization model for transit network timetable design to mitigate the randomness of traveling time by adding slack time. Trans- portation Research, Part C 52, pp. 15-31.
31. Xi, H., Son, Y.-J. (2012). Two-level modeling framework for pedestrian route choice and walking behaviors. Simulation Modelling Practice and Theory, No. 22, pp. 28-46.
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1. Ciszewski, T., Dębowska-Mróz, M., Ferensztajn-Galardos, E., Grad, B., Krajewska, R., Łukasik, Z., Rogowski, A., Wojciechowski, W. (2014). Analiza przemieszczeń i preferencji komunika¬cyjnych na obszarze ROF opracowanie zespołu UTH Radom (umowa NR 1/KM4/2014 z dnia 21 maja 2014 r. między SITK Oddział w Krakowie a UTH w Radomiu) w ramach projektu Zintegrowane planowanie transportu zrównoważonego miejskiego Radomskiego Obszaru Funkcjonalnego (umowa MPU-II/3302/4/2014 z dnia 22.04.2014 r. między Miejską Pracownią Urbanistyczną w Radomiu a SITK Oddział w Krakowie).
Press and occasional articles:
1. Borndorfer, R., Grotschel, M., Pfetsch, M.E. (2004). Models for Line Planning in Public Transport. ZIB-Report 04-10 (April), Berlin: Konrad-Zuse-Zentrum fur Informationstechnik Berlin.
2. Borndorfer, R., Grotschel, M., Pfetsch, M.E. (2007). A Column-Generation Approach to Line
Planning in Public Transport. Transportation Science, Vol. 41, No. 1, February, pp. 123-132, DOI 10.1287/trsc.1060.0161.
3. Cascetta, E., Papola, A., Marzano, V., Simonelli, F., Vitiello, I. (2013). Quasi-dynamic estimation of o-d flows from traffic counts: Formulation, statistical validation and performance analysis on real data. Transportation Research, Part B 55, pp. 171-187.
4. Ceder, A. (2011). Public-transport vehicle scheduling with multi vehicle type. Transportation Research, Part C 19, pp. 485-497.
5. Ceder, A., Net, Y.L., Coriat, C. (2009). Measuring Public Transport Connectivity Performance Applied in Auckland, New Zealand. Transportation Research Record: Journal of the Transportation Research Board, No. 2111, Transportation Research Board of the National Academies, Washington, D.C., pp. 139-147. DOI: 10.3141/2111-16.
6. Ceder, A., Tal, O. (2001). Designing Synchronization into Bus Timetables. Transportation Research Record, Vol. 1760, Iss. 1, pp. 28-33, DOI 10.3141/1760-04.
7. Chamier-Gliszczyński, N. (2015). Analiza struktury podróży na potrzeby logistyki miasta. Logistyka, No. 2, pp. 65-72.
8. Chamier-Gliszczyński, N., Bohdal, T. (2016). Mobilność na obszarze miejskim w ochronie środowiska. Rocznik Ochrona Środowiska, Vol. 18, (pp. 387-399.
9. Dębowska-Mróz, M., Rogowski, A. (2013). Analiza zmian natężenia ruchu drogowego na wybranych ciągach komunikacyjnych w Radomiu. Technika Transportu Szynowego - koleje, tramwaje, metro, No. 10, pp. 2953-2968.
10. Dębowska-Mróz, M., Zawisza, T. (2017). Ocena napełnienia samochodów osobowych w aspekcie poprawy wykorzystania przestrzeni transportowej w miastach. Autobusy, No. 12, pp. 1814-1818.
11. Guihaire, V., Hao, J.-K. (2010). Transit network timetabling and vehicle assignment for regu- lating authorities. Computers & Industrial Engineering, No. 59, pp. 16-23.
12. Iacono, M., Krizek, K.J., El-Geneidy, A. (2010). Measuring non-motorized accessibility: issues, alternatives, and execution. Journal of Transport Geography, No. 18, pp. 133-140.
13. Kieu, L.M., Bhaskar, A., Cools, M., Chung, E. (2017). An investigation of timed transfer coordination using event based multi agent simulation. Transportation Research, Part C 81, pp. 363-378.
14. Liu, T., Ceder, A. (2017). Integrated Public Transport Timetable Synchronization and Vehicle Scheduling with Demand Assignment: A Bi-objective Bi-level Model Using Deficit Function Approach. Transportation Research Procedia, No. 23, pp. 341-361.
15. Liu, Z., Shen, J., Wang, H., Yang, W. (2007). Regional Bus Timetabling Model with Synchro- nization. Journal of Transportation Systems Engineering and Information Technology, Vol. 7, No. 2, pp. 109-112.
16. Michaelis, M, Schobel, A. (2009). Integrating line planning, timetabling, and vehicle schedul- ing: a customer-oriented heuristic. Public Transport, No. 1, pp, 211-232.
17. Nair, R., Coffey, C., Pinelli, F., Calabrese, F. (2013). Large-Scale Transit Schedule Coordination Based on Journey Planner Requests. Transportation Research Record: Journal of the Transpor- tation Research Board, No. 2351, Transportation Research Board of the National Academies, Washington, D.C., pp. 65-75. DOI: 10.3141/2351-08.
18. Nishiuchia, H., Todorokib, T., Kishib, Y. (2015). A Fundamental Study on Evaluation of Pub- lic Transport Transfer Nodes by Data Envelop Analysis Approach Using Smart Card Data. Transportation Research Procedia, No. 6, pp. 391-401.
19. Numov, V., Samchuk, G. (2017). Class Library for Simulations of Passenger Transfer Nodes as Elements of the Public Transport System. Procedia Engineering, No. 187, pp. 77-81.
20. Omar, J. Ibarra-Rojas, O.J., Yasmin, A. Rios-Solis, Y.A. (2012). Synchronization of bus time- tabling. Transportation Research, Part B 46, pp. 599-614.
21. Oziomek, J., Rogowski, A. (2018). Improvement of Regularity of Urban Public Transport Lines by Means of Intervals Synchronization. Transport Problems, Vol. 13, Iss. 4, pp. 91-102, DOI: 10.20858/tp.2018.13.4.9.
22. Pecenik, P. (2017). Węzły przesiadkowe w Warszawie. Zeszyty Naukowe Uczelni Vistula, No. 53 (2), Architektura, pp. 143-153, Akademia Finansów i Biznesu Vistula w Warszawie.
23. Rahman, K., Ghani, N.A., Kamil, A.A., Mustafa, A., Chowdhury, A.K. (2013). Modelling Pedestrian Travel Time and the Design of Facilities: A Queuing Approach. PLOS-ONE, Vol. 8, Iss. 5, May, pp. 1-13. www.plosone.org.
24. Schobel, A. (2012). Line planning in public transportation: models and methods. OR Spectrum, No. 34, pp. 491-510, DOI 10.1007/s00291-011-0251-6.
25. Schobel, A. (2017). An eigenmodel for iterative line planning, timetabling and vehicle scheduling in public transportation. Transportation Research, Part C 74, pp. 348-365.
26. Serge, P., Hoogendoorn, S.P., Bovy, P.H.L. (2005). Pedestrian Travel Behavior Modeling. Networks and Spatial Economics, No. 5, pp. 193-216.
27. Sierpiński, G., Staniek, M., Celiński, I., Czech, P., Barcik, J. (2015). Identification of pedestrian travel in modeling of modal split and transport accessibility. Logistyka, No. 4, pp. 1495-1502.
28. Varga, B., Tettamanti, T., Kulcsar, B. (2018). Optimally combined headway and timetable reli- able public transport system. Transportation Research, Part C 92, pp. 1-26.
29. Wachowiak, W. (2018). Integracja podsystemów transportowych w węzłach przesiadkowych komunikacji publicznej Poznania w oparciu o kolejowe dworce miejskie. Biuletyn KPZK PAN, Vol. 270, pp. 82-106.
30. Wu, Y., Tang, J., Yu, Y., Pan, Z. (2015). A stochastic optimization model for transit network timetable design to mitigate the randomness of traveling time by adding slack time. Trans- portation Research, Part C 52, pp. 15-31.
31. Xi, H., Son, Y.-J. (2012). Two-level modeling framework for pedestrian route choice and walking behaviors. Simulation Modelling Practice and Theory, No. 22, pp. 28-46.
32. Xiao, M., Chien, S., Hu, D. (2016). Optimizing coordinated transfer with probabilistic vehicle arrivals and passengers' walking time. Journal of Advanced Transportation, No. 50, pp. 2306-2322.
33. Yamamoto, T., Takamura, S., Morikawa, T. (2018). Structured random walk parameter for heterogeneity in trip distance on modeling pedestrian route choice behavior at downtown area. Travel Behaviour and Society, No. 11, pp. 93-100.