Estimation of Transport Potential in Regional Rail Passenger Transport by Using the Innovative Mathematical-Statistical Gravity Approach
Abstract
:1. Introduction
- vij
- passenger flow between i-th and j-th places;
- k
- gravity constant;
- Qi
- source/origin potential of i-th place;
- Zj
- destination potential of j-th place;
- wij
- deterrence function.
2. Materials and Methods
- 1.
- Determination of actual transport needs.
- 2.
- Determination of current travel motives.
- 3.
- Classification of the transport service type.
- 4.
- Definition of factors affecting transport services.
- 5.
- Determination of transport potential.
- 6.
- Determination of the range of railway infrastructure.
- 7.
- Proposal for final timetable standards.
- 8.
- Final timetable construction.
3. Results
3.1. Transport Potential Based Formula
- Number of inhabitants belonging to the track line section under review.
- Momentum of the population.
- Transport distance.
- Availability of the railway station and stop.
- Overlapping with road.
- Continuity of the assessed section to other railway lines.
- The monitored area’s attractiveness.
3.2. Assignment of the Resulting Value of the Range of Transport Services
- The scale will be determined based on the calculation of the resulting value of Kp on the selected 30 transport sessions. Subsequently, assigning the resulting values to the different ranges of traffic, which will be marked with Roman numerals (I–X), including determining the optimum number of trains and the optimal number of seats;
- The sample of 30 transport sessions contains all transport sessions (track sections between individual centers) on Slovak railway networks in the Zilina and Trencin regions (with the exception of the Trencianska Tepla–Trencianske Teplice railway line). In the next step railway lines in western part of Slovakia (Bratislava–Trnava, Bratislava–Galanta, Bratislava–Kvetoslavov, Kuty–Skalica, Zohor–Zahorska Ves, Zohor–Plavecky Mikulas, Jablonica–Brezova pod Bradlom and Zbehy–Radosina), in central Slovakia (Breznicka–Katarinska Huta) and in eastern Slovakia (Plesivec–Slavosovce, Kosice–Kechnec, and Banovce nad Ondavou–Velke Kapusany) were analyzed. This selection covers transport sessions with different ranges of traffic: extremely high, extremely low and medium high transport potential are expected to make the subsequent data as relevant as possible;
- The following scale shall be based on the resulting Kp values on the analyzed transport lines, and the standard deviation shall be calculated from each of the resulting Kp values as a standard deviation:The number of monitored transport sessions is N for each session potential xi and the average value of Kp is .
- After the calculation, the individual ranges of the traffic services are determined by deducting the standard deviation (or its half value) from the average until the zero value is reached and then adding the same number of particular values, which can be express by:
- In the research 10 ranges of traffic service with 10 equally wide intervals were established, so it is preferable to consider half of the standard deviation, using this formula:
- However, after this step, it may be necessary to modify the said interval width, as it is very important to adjust the scale in such a way that it actually corresponds to the individual values that can be achieved on each transport route;
- Calculations of the transport potential Kp are given in Table 1, in which the main characteristics of the transport session (line type, number of line tracks, line lengths, as well as subsequent calculations of arithmetic mean and standard deviation) are expressed. The sessions are listed from the highest value to the lowest value of Kp potential.
- Following the width determination of the resulting Kp intervals for each range of service, the recommended daily number of pairs of all links, the recommended daily capacity, and the total number of all seats in all vehicles on session links shall be assigned to these ranges. The recommended capacity interval for individual ranges of transportation services is relatively wide, since it is necessary to consider individual extreme values of capacity of individual links. In fact, it is possible that one regional link can have a capacity of 50 seats (appropriate for motor unit) and another regional link can have a capacity of 480 seats (appropriate for a train set of wagons);
- For segments of regional and suburban transport services, recommended regional values are introduced in the Table 4; it is expressed in specified optimal number of train pairs as well optimal number of seats on all vehicles operated on the transportation session.
- Whether the region is attractive for tourism and whether there are tourist attractions (recreational, spa, sports, cultural, commercial, social, or other) close to the railway line;
- Whether most jobs, schools, universities, offices, etc. are concentrated in the region (from these centers it is necessary to ensure optimal transportation service);
- Whether the railway line is in direct parallel with the road;
- Whether the transport route is part of a railway line which is of important transit significance or only of local significance and the railway line is terminated at the head station;
- What is the general transport momentum trend in the region under review (but this data is rarely available).
4. Discussion and Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- KOM/2011/144. Transport White Paper 2011 Roadmap to a Single European Transport Area–Towards a Competitive and Resource Efficient Transport System. 2016. Available online: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2011:0144:FIN:EN:PDF (accessed on 15 March 2020).
- Szkopinski, J. The Certain Approach to the Assessment of Interoperability of Railway Lines. Arch. Transp. 2014, 1, 65–75. [Google Scholar] [CrossRef]
- Iwnicki, S.; Spiryagin, M.; Cole, C.; McSweeney, T. Handbook of Railway Vehicle Dynamics, 2nd ed.; CRC Press: Boca Raton, FL, USA, 2019; p. 893. [Google Scholar]
- Song, Y.; Liu, Z.; Rønnquist, A.; Navik, P.; Liu, Z. Contact Wire Irregularity Stochastics and Effect on High-speed Railway Pantograph-Catenary Interactions. IEEE Trans. Instrum. Meas. 2020. [Google Scholar] [CrossRef]
- Zitricky, V.; Gasparik, J.; Peceny, L. The methodology of rating quality standards in the regional passenger transport. Transp. Probl. 2015, 10, 59–72. [Google Scholar] [CrossRef] [Green Version]
- Dedik, M.; Dlugos, M.; Luptak, V.; Blaho, P. Optimization of empirical models of transport planning in railway transport. Transp. Commun. 2017, 5, 1–5. [Google Scholar]
- Eboli, L.; Mazzulla, G. Relationships between rail passengers’ satisfaction and service quality: A framework for identifying key service factors. Public Transp. 2015, 2, 185–201. [Google Scholar] [CrossRef]
- Janos, V.; Kriz, M. Pragmatic approach in regional rail transport planning. Sci. J. Sil. Univ. Technol. Ser. Transp. 2018, 100, 35–43. [Google Scholar]
- Sun, Q.; Wang, X.; Ma, F.; Han, Y.; Cheng, Q. Synergetic Effect and Spatial-Temporal Evolution of Railway Transportation in Sustainable Development of Trade: An Empirical Study Based on the Belt and Road. Sustainability 2019, 11, 1721. [Google Scholar] [CrossRef] [Green Version]
- Banister, D. The sustainable mobility paradigm. Transp. Policy 2008, 15, 73–80. [Google Scholar] [CrossRef]
- Sipus, D.; Abramovic, B. Tariffing in Integrated Passenger Transport Systems: A Literature Review. Promet–Traffic Transp. 2018, 6, 745–751. [Google Scholar] [CrossRef]
- Hranicky, M.P.; Vojtek, M.; Siroky, J.; Cerna, L. Sustainable railway passenger transport on regional level. In Transport Means: Proceedings of the International Scientific Conference; Kaunas University of Technology: Kaunas, Lithuania, 2019; pp. 814–819. [Google Scholar]
- Cempirek, V.; Nachtigall, P.; Novak, P.; Pluhar, M. The comparison of public road and railway transport costs. ICTTE 2016, 81, 855–860. [Google Scholar]
- Danis, J.; Dolinayova, A.; Cerna, L.; Zitricky, V. Impact of the economic situation in the Slovak Republic on performances of railway transport. Period. Polytech. Transp. Eng. 2018, 47, 118–123. [Google Scholar] [CrossRef] [Green Version]
- Blaskovic, Z.J.; Abramovic, B.; Sipus, D. A Strategic Model of Sustainable in the city of Zagreb and its Surrounding Area. II Int. J. Traffic Transp. Eng. 2017, 7, 430–442. [Google Scholar]
- Fedorko, G.; Molnar, V.; Strohmandl, J.; Vasil, M. Development of Simulation Model for Light-Controlled Road Junction in the Program Technomatix Plant Simulation. Transp. Means 2015, 2015, 466–469. [Google Scholar]
- Bartuska, L.; Biba, V.; Kampf, R. Modeling of Daily Traffic Volumes on Urban Roads. In 3rd International Conference on Traffic and Transport Engineering (ICTTE2016); City Net Scientific Research Center: Belgrade, Serbia, 2016; pp. 900–905. [Google Scholar]
- Cerna, L.; Zitricky, V.; Danis, J. The methodology of selecting the transport mode for companies on the Slovak transport market. Open Eng. 2017, 7, 6–13. [Google Scholar] [CrossRef]
- Nedeliakova, E.; Kuka, A.; Sulko, P.; Hranicky, M. An innovative approach to monitoring the synergies of extraordinary events in rail transport. Transp. Means 2018, 2018, 28–32. [Google Scholar]
- Kendra, M.; Skorupa, M.; Zitricky, V. Potential of regional trains within the logical transport-geographic regions of Slovakia. In Proceedings of the 8th International Scientific Conference CMDTUR, Žilina, Slovakia, 4–5 October 2018; pp. 172–177. [Google Scholar]
- Rybicka, I.; Stopka, O.; Luptak, V.; Chovancova, M.; Drozdziel, P. Application of the methodology related to the emission standard to specific railway line in comparison with parallel road transport. In MATEC Web of Conferences; EDP Sciences: Les Ulis, France, 2018; Volume 244, pp. 1–7. [Google Scholar]
- Poliak, M.; Poliakova, A.; Mrnikova, M.; Simurkova, P.; Jaskiewicz, M.; Jurecki, R. The competitiveness of public transport. J. Compet. 2017, 9, 81–97. [Google Scholar] [CrossRef]
- Ponicky, J.; Camaj, J.; Kendra, M. Possibilities of Simulation Tools for Describing Queuing Theory and Operations Service Lines in Railway Passenger Transport. Int. Conf. Eng. Sci. Manag. 2016, 44, 191–194. [Google Scholar]
- Skrucany, T.; Kendra, M.; Skorupa, M. Comparison of chosen environmental aspects in individual road transport and railway passenger transport. Mod. Safe Transp. 2017, 192, 806–811. [Google Scholar] [CrossRef]
- Bartuska, L.; Cerna, L.; Danis, J. Costs comparison and the possibilities of increasing the transport capacity with a selection of the appropriate railway wagons. Nase More 2017, 63, 93–97. [Google Scholar]
- Kvizda, M. Policy of Railways Tender-Theory, Experience and Practice application; Masaryk University: Brno, Czech Republic, 2016; p. 202. [Google Scholar]
- Kendra, M.; Babin, M.; Sulko, P. Interaction between Railway Infrastructure Parameters and Quality of Transportation Services; Technical University Academic Publishing House: Sofia, Bulgaria, 2013; pp. 95–97. [Google Scholar]
- Gasparik, J.; Luptak, V.; Kurenkov, P.V.; Mesko, P. Methodology for assessing transport connections on the integrated transport network. Commun. Sci. Lett. Univ. Zilina 2017, 19, 61–67. [Google Scholar]
- Gasparik, J.; Siroky, J.; Peceny, L.; Halas, M. Methodology for assessing the quality of rail connections on the network. Commun. Sci. Lett. Univ. Zilina 2014, 16, 25–30. [Google Scholar]
- Gasparik, J.; Sulko, P. Technology of Railway Transportation, Line Transport Processes; University of Zilina: Zilina, Slovakia, 2016. [Google Scholar]
- Masek, J.; Kendra, M.; Camaj, J. Model of the transport capacity of the train and railway track based on used types of wagons. In Proceedings of the Transport Means-Proceedings of the 20th International Conference, Kaunas, Lithuania, 5–7 October 2016; pp. 584–588. [Google Scholar]
- Hansen, I.A. Review of planning and capacity analysis for stations with multiple platforms. Rail Transp. Plan. Manag. 2017, 6, 313–330. [Google Scholar]
- Polinder, G.J.; Breugem, T.; Dollevoet, T.; Maroti, G. An adjustable robust optimization approach for periodic timetabling. Transp. Res. Part B-Methodical 2019, 128, 50–68. [Google Scholar] [CrossRef] [Green Version]
- Drabek, M.; Janos, V.; Michl, Z. Quantitative Determination of Bottlenecks in Railway Networks with Periodic Service. In Proceedings of the 20th International Conference Transport Means, Kaunas, Lithuania, 5–7 October 2016; pp. 594–598. [Google Scholar]
- Drabek, M. Irregularities in Czech Integrated Periodic Timetable. In MATEC Web of Conferences; EDP Sciences: Les Ulis, France, 2018; Volume 235, pp. 51–54. [Google Scholar]
- Kampf, R.; Stopka, O.; Bartuska, L.; Zeman, K. Circulation of vehicles as an important parameter of public transport efficiency. In Proceedings of the 19th International Conference Transport Means, Kaunas, Lithuania, 22–23 October 2015; pp. 143–146. [Google Scholar]
- Lill, E. The Travel Law and Its Applications to Rail Transport (In German); Spielhagen&Schurich: Wien, Austria, 1891. [Google Scholar]
- Odlyzko, A. The Forgotten Discovery of Gravity Models and the Inefficiency of Early Railway Networks. OEconomial 2015, 5, 157–192. [Google Scholar] [CrossRef]
- Gunnarsson, S.O. Studies in travel behaviour and mobility management need a special scientific discipline: “Mobilistics”. IATSS Res. 2000, 24, 69–75. [Google Scholar] [CrossRef] [Green Version]
- Horbachov, P.; Svichynskyi, S. Theoretical substantiation of trip length distribution for home-based work trips in urban transit systems. J. Transp. Land Use 2018, 11, 593–632. [Google Scholar] [CrossRef] [Green Version]
- Dedik, M.; Kendra, M.; Čechovič, T.; Vojtek, M. Determining traffic potential as an important part of sustainable railway passenger transport. IOP Conf. Ser. Mater. Sci. Eng. 2019, 664, 012030. [Google Scholar] [CrossRef] [Green Version]
Transport Session | Railway Line Type | Tracks Number of Line | Railway Line Length (km) | Transport Potential Coefficient Kp | Range of Transportation Services |
---|---|---|---|---|---|
Bratislava–Trnava | Main | 2 | 46 | 2501.94 | IX |
Bratislava–Kvetoslavov | Main | 1 | 22 | 2369.93 | VIII |
Cadca–Makov | Regional | 1 | 26 | 2331.19 | VIII |
Kralovany–Trstena | Regional | 1 | 56 | 1959.70 | VII |
Trencianska Tepla–Horne Srnie | Regional | 1 | 8 | 1821.07 | VII |
Chynorany–Prievidza | Main | 1 | 34 | 1814.27 | VII |
Cadca–Zwardon | Main | 1 | 22 | 1778.25 | VI |
Zilina–Rajec | Regional | 1 | 21 | 1739.25 | VI |
Bratislava–Galanta | Main | 2 | 49 | 1445.98 | V |
Trencin–Puchov | Main | 2 | 35 | 1421.58 | V |
Zilina–Liptovsky Mikulas | Main | 2 | 83 | 1376.77 | IV |
Zilina–Cadca | Main | 2 | 30 | 1341.99 | IV |
Prievidza–Nitrianske Pravno | Regional | 1 | 11 | 1265.99 | IV |
Trencin–Chynorany | Main | 1 | 49 | 1111.57 | III |
Nemsova–Lednicke Rovne | Regional | 1 | 17 | 1103.28 | III |
Puchov–Zilina | Main | 2 | 44 | 1070.74 | III |
Kuty–Skalica na Slovensku | Regional | 1 | 26 | 1056.32 | III |
Jablonica–Brezova pod Bradlom | Regional | 1 | 12 | 912.26 | II |
Zohor–ZahorskaVes | Regional | 1 | 14 | 882.75 | II |
Puchov–Horni Lidec | Main | 2 | 28 | 815.21 | II |
Martin–Horna Stubna | Main | 2 | 32 | 811.38 | II |
Prievidza–Horna Stubna | Regional | 1 | 37 | 783.20 | II |
Zbehy–Radosina | Regional | 1 | 20 | 777.65 | II |
Banovce n/O–Velke Kapusany | Regional | 1 | 26 | 729.84 | II |
Kosice–Kechnec | Main | 1 | 28 | 725.81 | II |
Nove Mesto n/V–Myjava | Regional | 1 | 36 | 705.34 | II |
Zohor–Plavecky Mikulas | Regional | 1 | 35 | 666.51 | I |
Plesivec–Slavosovce | Regional | 1 | 24 | 616.03 | I |
Breznicka–Katarinska Huta | Regional | 1 | 10 | 577.09 | I |
Myjava–Velka n/V | Regional | 1 | 14 | 290.56 | I |
Average value Kp | 1226.78 | ||||
Standard deviation from individual values δ | 583.482 | ||||
Half of the standard deviation δ/2 | 291.741 |
Range of Transportation Service | Interval Width |
---|---|
I | 0–351.55 |
II | 351.56–643.29 |
III | 643.30–935.03 |
IV | 935.04–1226.77 |
V | 1226.78–1518.51 |
VI | 1518.52–1810.25 |
VII | 1810.26–2101.99 |
VIII | 2102.00–2393.74 |
IX | 2393.75–2685.48 |
X | 2685.49 and more |
Range of Transportation Service | Interval Width |
---|---|
I | 0–700 |
II | 701–1000 |
III | 1001–1200 |
IV | 1201–1400 |
V | 1401–1600 |
VI | 1601–1800 |
VII | 1801–2000 |
VIII | 2001–2500 |
IX | 2501–3000 |
X | 3001 and more |
Range of Transportation Service | Transport Potential Range Kp | Optimal Number of Train Pairs in Both Directions | Optimal Number of Seats for all Lines in Both Directions |
---|---|---|---|
I | 0–700 | 4 | up to 500 seats |
II | 701–1000 | 5–6 | 250–2700 |
III | 1001–1200 | 7–10 | 350–4500 |
IV | 1201–1400 | 11–15 | 550–6800 |
V | 1401–1600 | 16–20 | 800–9000 |
VI | 1601–1800 | 21–25 | 1050–11,300 |
VII | 1801–2000 | 26–30 | 1300–13,500 |
VIII | 2001–2500 | 31–39 | 1600–17,600 |
IX | 2501–3000 | 40–49 | 2000–22,100 |
X | 3001 and more | 50 and more | 2500 and more |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gasparik, J.; Dedik, M.; Cechovic, L.; Blaho, P. Estimation of Transport Potential in Regional Rail Passenger Transport by Using the Innovative Mathematical-Statistical Gravity Approach. Sustainability 2020, 12, 3821. https://doi.org/10.3390/su12093821
Gasparik J, Dedik M, Cechovic L, Blaho P. Estimation of Transport Potential in Regional Rail Passenger Transport by Using the Innovative Mathematical-Statistical Gravity Approach. Sustainability. 2020; 12(9):3821. https://doi.org/10.3390/su12093821
Chicago/Turabian StyleGasparik, Jozef, Milan Dedik, Lukas Cechovic, and Peter Blaho. 2020. "Estimation of Transport Potential in Regional Rail Passenger Transport by Using the Innovative Mathematical-Statistical Gravity Approach" Sustainability 12, no. 9: 3821. https://doi.org/10.3390/su12093821
APA StyleGasparik, J., Dedik, M., Cechovic, L., & Blaho, P. (2020). Estimation of Transport Potential in Regional Rail Passenger Transport by Using the Innovative Mathematical-Statistical Gravity Approach. Sustainability, 12(9), 3821. https://doi.org/10.3390/su12093821