Modeling of traffic flows in the justification of projects of road construction in conditions of concession
DOI:
https://doi.org/10.15587/1729-4061.2020.193463Keywords:
toll, road construction concessions, traffic flow, toll road, road constructionAbstract
A method for studying the expected traffic flow distribution between toll and alternative roads based on user behavior principles is proposed. It is assumed that the user’s behavior is rational: he always chooses the most suitable option. The proposed model takes into account the cost of fuel and lubricants, the time and toll of toll and alternative routes. This means that if the cost of toll and alternative roads is the same, the user will not care which route to choose. By changing the toll for 1 km, it is possible to affect the cost of the “expenses for the toll route” component and the corresponding traffic flow. Saturation of the road with vehicles will occur until, due to the complication of traffic on it, the total costs exceed those when driving another road.
Analytical models are developed and proposed for:
1) toll determination;
2) traffic flow distribution between toll and alternative roads.
The models provided information on the expected traffic flow distribution between toll and alternative routes. It is necessary for:
1) economic justification of project attractiveness for private investors and project feasibility under concession;
2) determination of traffic intensity, below which it is impractical for the authorities to set concession payments under the concession agreement.
The use of the models proposed by the authors is presented on the materials of the project of the construction phase of the Great Kyiv Ring Road (Ukraine)
References
- Dehghan Shabani, Z., Safaie, S. (2018). Do transport infrastructure spillovers matter for economic growth? Evidence on road and railway transport infrastructure in Iranian provinces. Regional Science Policy & Practice, 10 (1), 49–63. doi: https://doi.org/10.1111/rsp3.12114
- Karpenko, O. O., Palyvoda, O. M., Bondar, N. M. (2018). Modelling the integral performance of transport and logistics clusters. Scientific Bulletin of Polissia, 2 (1 (13)), 155–160. doi: https://doi.org/10.25140/2410-9576-2018-2-1(13)-155-160
- Market Update. Review of the European PPP Market in 2018. The European PPP Expertise Centre (EPEC), 14.
- Public-Private Partnership Monitor (2019). Asian Development Bank, 910. doi: https://doi.org/10.22617/tcs190020-2
- Garemo, N., Hjerpe, M., Halleman, B. (2018). A better road to the future: Improving the delivery of road infrastructure across the world. McKinsey&Company, 32. Available at: https://www.mckinsey.com/~/media/mckinsey/industries/capital%20projects%20and%20infrastructure/our%20insights/improving%20the%20delivery%20of%20road%20infrastructure%20across%20the%20world/a-better-road-to-the-future-web-final.ashx
- Maslova, S. (2016). UNECE PPP Best Practice Guide for Road Sector. International PPP Forum: “Implementing the United Nations 2030 Agenda for Sustainable Development through effective, people-first Public-Private Partnerships”. Available at: https://www.unece.org/fileadmin/DAM/ceci/documents/2016/PPP/Forum_PPP-SDGs/Presentations/Svetlana_Maslova-Best_Practice_Guide_for_Roads_Sector.pdf
- Private Participation in Infrastructure (PPI) – World Bank Group. Available at: https://ppi.worldbank.org/en/snapshots/sector/toll-roads
- Robert, J. (2001). Models for the financing of regional infrastructure and development projects, with a particular attention to the countries of Central and Eastern Europe – Public-private partnerships in spatial development policy. European regional planning (CEMAT), No. 63. Available at: https://rm.coe.int/16804895a3
- Iyer, K. C., Sagheer, M. (2011). A real options based traffic risk mitigation model for build-operate-transfer highway projects in India. Construction Management and Economics, 29 (8), 771–779. doi: https://doi.org/10.1080/01446193.2011.597412
- Ma, G., Du, Q., Wang, K. (2018). A Concession Period and Price Determination Model for PPP Projects: Based on Real Options and Risk Allocation. Sustainability, 10 (3), 706. doi: https://doi.org/10.3390/su10030706
- Shvetsov, V. I. (2003). Mathematical Modeling of Traffic Flows. Automation and Remote Control, 64, 1651–1689. doi: https://doi.org/10.1023/A:1027348026919
- Ehlert, A., Bell, M. G. H., Grosso, S. (2006). The optimisation of traffic count locations in road networks. Transportation Research Part B: Methodological, 40 (6), 460–479. doi: https://doi.org/10.1016/j.trb.2005.06.001
- Sánchez-Cambronero, S., Rivas, A., Barba, R. M., Ruiz-Ripoll, L., Gallego, I., Menéndez, J. M. (2016). A Methodology to Model a Traffic Network Which have their Field Data Obtained by Plate Scanning Technique. Transportation Research Procedia, 18, 341–348. doi: https://doi.org/10.1016/j.trpro.2016.12.046
- Soliño, A. S., Lara Galera, A. L., Colín, F. C. (2017). Measuring uncertainty of traffic volume on motorway concessions: a time-series analysis. Transportation Research Procedia, 27, 3–10. doi: https://doi.org/10.1016/j.trpro.2017.12.006
- Apronti, D., Ksaibati, K., Gerow, K., Hepner, J. J. (2016). Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods. Journal of Traffic and Transportation Engineering (English Edition), 3 (6), 493–506. doi: https://doi.org/10.1016/j.jtte.2016.02.004
- Sperry, B. R., Mahmood, S., Naik, B. (2018). Land Development and Traffic Composition at Rural Interstate Highway Interchanges in Ohio. Journal of Transportation Engineering, Part A: Systems, 144 (7), 04018029. doi: https://doi.org/10.1061/jtepbs.0000154
- Horbachov, P., Samchuk, G. (2014). Analysis of transport systems development forecasting method. Eastern-European Journal of Enterprise Technologies, 2 (3 (68)), 29–34. doi: https://doi.org/10.15587/1729-4061.2014.23152
- Honcharenko, F. P. (2015). Prohnozuvannia intensyvnosti rukhu avtomobilnymy dorohamy. Avtoshliakhovyk Ukrainy, 1-2, 57–59. Available at: http://nbuv.gov.ua/UJRN/au_2015_1-2_18
- MR A.2.1-218-02070915-729:2008. Metodychni rekomendatsiyi z vyznachennia isnuiuchoi ta prohnozuvannia perspektyvnoi intensyvnosti rukhu.
- Haghani, M., Shahhoseini, Z., Sarvi, M. (2016). Path sets size, model specification, or model estimation: Which one matters most in predicting stochastic user equilibrium traffic flow? Journal of Traffic and Transportation Engineering (English Edition), 3 (3), 181–191. doi: https://doi.org/10.1016/j.jtte.2015.09.007
- Wardrop, J. G. (1952). Road paper. Some theoretical aspects of road traffic research. Proceedings of the Institution of Civil Engineers, 1 (3), 325–362. doi: https://doi.org/10.1680/ipeds.1952.11259
- McFadden, D. (1974). The measurement of urban travel demand. Journal of Public Economics, 3 (4), 303–328. doi: https://doi.org/10.1016/0047-2727(74)90003-6
- Fischer, M. M., Nijkamp, P. (1987). From static towards dynamic discrete choice modelling. Regional Science and Urban Economics, 17 (1), 3–27. doi: https://doi.org/10.1016/0166-0462(87)90066-4
- De Carvalho, M. C. M., Dougherty, M. S., Fowkes, A. S., Wardman, M. R. (1998). Forecasting travel demand: a comparison of logit and artificial neural network methods. Journal of the Operational Research Society, 49 (7), 717–722. doi: https://doi.org/10.1057/palgrave.jors.2600590
- Dafermos, S. (1980). Traffic Equilibrium and Variational Inequalities. Transportation Science, 14 (1), 42–54. doi: https://doi.org/10.1287/trsc.14.1.42
- Nagurney, A. B. (1984). Comparative tests of multimodal traffic equilibrium methods. Transportation Research Part B: Methodological, 18 (6), 469–485. doi: https://doi.org/10.1016/0191-2615(85)90013-x
- Smith, M. J. (1979). The existence, uniqueness and stability of traffic equilibria. Transportation Research Part B: Methodological, 13 (4), 295–304. doi: https://doi.org/10.1016/0191-2615(79)90022-5
- Dombalyan, A., Kocherga, V., Semchugova, E., Negrov, N. (2017). Traffic Forecasting Model for a Road Section. Transportation Research Procedia, 20, 159–165. doi: https://doi.org/10.1016/j.trpro.2017.01.040
- Li, J., Mao, P., Dai, Z., Zhang, J. (2018). Traffic Allocation Mode of PPP Highway Project: A Risk Management Approach. Advances in Civil Engineering, 2018, 1–12. doi: https://doi.org/10.1155/2018/7193948
- Musso, A., Piccioni, C., Tozzi, M., Godard, G., Lapeyre, A., Papandreou, K. (2013). Road Transport Elasticity: How Fuel Price Changes can Affect Traffic Demand on a Toll Motorway. Procedia - Social and Behavioral Sciences, 87, 85–102. doi: https://doi.org/10.1016/j.sbspro.2013.10.596
- Garcı́a, R., Marı́n, A. (2005). Network equilibrium with combined modes: models and solution algorithms. Transportation Research Part B: Methodological, 39 (3), 223–254. doi: https://doi.org/10.1016/j.trb.2003.05.002
- Batista, S. F. A., Zhao, C.-L., Leclercq, L. (2018). Effects of Users’ Bounded Rationality on a Traffic Network Performance: A Simulation Study. Journal of Advanced Transportation, 2018, 1–20. doi: https://doi.org/10.1155/2018/9876598
- Li, M., Huang, H.-J., Liu, H. (2018). Stochastic Route Choice Equilibrium Assignment for Travelers with Heterogeneous Regret Aversions. Journal of Management Science and Engineering, 3 (1), 1–15. Available at: https://www.sciencedirect.com/science/article/pii/S2096232019300423
- Zhang, Z.-Z., Tang, T.-Q., Huang, H.-J. (2019). Modeling the social-influence-based route choice behavior in a two-route network. Physica A: Statistical Mechanics and Its Applications, 531, 121744. doi: https://doi.org/10.1016/j.physa.2019.121744
- De Grange, L., Marechal, M., González, F. (2019). A Traffic Assignment Model Based on Link Densities. Journal of Advanced Transportation, 2019, 1–20. doi: https://doi.org/10.1155/2019/5282879
- Cheung, K., Polak, J. W. (2009). A Bayesian approach to modelling uncertainty in transport infrastructure project forecasts. AET. Available at: https://aetransport.org/public/downloads/juHGZ/4104-514ec5ca67ff1.pdf
- Semenov, V. V. (2004). Matematicheskoe modelirovanie dinamiki transportnyh potokov megapolisa. Available at: https://keldysh.ru/papers/2004/prep34/prep2004_34.html
- M 218-02070915-674:2010. Metodika opredelenie urovnya zagruzhennosti i propusknoy sposobnosti avtomobil'nyh dorog.
- Bondar, N. (2014). Justification of fares on toll road carriers for food. Ukrainian Food Journal, 3 (1), 19–25.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Nataliia Bondar, Stanislav Gendek, Oksana Karpenko, Tamara Navrotskaya, Victoria Sukmaniuk
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.