Forecasting the mobility parameters of the inhabitants of suburban areas

TT.
2021;
: 1-12
https://doi.org/10.23939/tt2021.01.001
Received: March 16, 2021
Accepted: April 09, 2021
1
National University of Water and Environmental Engineering

Potential mobility that meets the requirements of population displacement is determined following the biological and social needs, socio-economic characteristics, production necessity, and cultural needs. Because of the multifactor character and complexity of relationships, it is impossible to determine the potential mobility by a calculation method. The feasibility of different target movements, depending on their distance, is regarded by rural populations differently. Each rural settlement is located among many other rural and urban settlements with an individual quantitative and qualitative set of social, cultural, and industrial potential. With the developed road network and public transport system, the population selects the center of gravity with the limitations imposed by this transport system and is based on subjective considerations about the quality of service. The distribution of urban residents’ movements to the rural areas is affected by the size of the city, movement distance, movement purpose, i.e. the same factors as rural residents’ movement to cities. The difference is that the radius of urban residents’ movements distribution is much smaller. Thus, the zone of intensive and regular movements in the working day cycle covers only nearest to cities rural area with a radius of 15 km. On weekends, due to guest visits and holiday trips, the radius of this zone extends approximately 1,5-2 times. Based on the links distribution, the scatter band of the initial and final points of movement can be obtained. Since the density of scattering varies with respect to settlements, then we can allocate the territorial units that will make service zone on their sets. Research results can be an integral part of comprehensive studies of determining the transport links density, hubs of passenger flows’ origin, and suppression to construct mathematical models of the most efficient passenger transport system operation.

1. European Comission. (2016). Horizon 2020 - Smart, Green and Integrated transport. Important Notice on the Second Horizon 2020 Work Programme, 2017 (July 2016), 129. (in English)

2. Li, Y. & Voege, T. (2017) Mobility as a Service (MaaS): Challenges of Implementation and Policy Required. Journal of Transportation TechnologiesVolume 7, 95-106. doi: 10.4236/jtts.2017.72007. (in English) https://doi.org/10.4236/jtts.2017.72007

3. Yatskiv, I., Pticina, I., & Savrasovs, M. (2012). Urban Public Transport System's Reliability Estimation Using Microscopic Simulation, Transport and Telecommunication JournalVolume 13(3), 219-228. doi: 10.2478/v10244-012-0018-4 (in English) https://doi.org/10.2478/v10244-012-0018-4

4. Gidebo, F., & Szpytko, J. (2019). Reliability Assessment of the Transport System, Addis Ababa Case Study, Journal of KONBiNVolume 49(4), 27-36. doi: 10.2478/jok-2019-0073. (in English) https://doi.org/10.2478/jok-2019-0073

5. Khitrov, I., & Tkhoruk, Y. (2020). Formation and Distribution Flows of External Transport in the City. In Reliability and Statistics in Transportation and Communication: Selected Papers from the 19th International Conference on Reliability and Statistics in Transportation and Communication, RelStat’19, 16-19 October 2019, Riga, Latvia (Vol. 117, p. 141). Springer Nature. (in English) https://doi.org/10.1007/978-3-030-44610-9_15

6. Tkhoruk Y., Kucher O., Holotiuk M., Krystopchuk M. & Tson O. (2019) Modeling of assessment of reliability transport systems. Proceedings of ICCPT 2019 (Tern., May 28-29, 2019), pp. 204-210. (in English)

7. Dumbliauskas, V. (2019). Development and application of tour-based travel demand model for planning of urban transport networks (Doctoral dissertation, VGTU leidykla „Technika “) (in English) https://doi.org/10.20334/2019-004-M

8. Raux, C. (2003). A systems dynamics model for the urban travel system. In AET. European Transport Conference 2003–ETC 2003, 8-10 october 2003, Strasbourg (pp. 32-p). AET. (in English)

9. Ortúzar, J. de D. & Willumsen, L. G. (2011) "Modelling Transport". Fourth Edition, John Wiley and Sons, Chichester. (in English) https://doi.org/10.1002/9781119993308

10. Balcombe, R., Mackett, R., Paulley, N., Preston, J., Shires, J., Titheridge, H. & et al. (2004). The demand for public transport: a practical guide. (in English)

11. Bhat, C. R., & Koppelman, F. S. (1999). Activity-based modeling of travel demand. In Handbook of transportation Science (pp. 35-61). Springer, Boston, MA. (in English) https://doi.org/10.1007/978-1-4615-5203-1_3

12. Dianat, L., Habib, K. N., & Miller, E. J. (2020). Modeling and forecasting daily non-work/school activity patterns in an activity-based model using skeleton schedule constraints. Transportation research part A: policy and practice133, 337-352. doi:10.1016/j.tra.2020.01.017. (in English) https://doi.org/10.1016/j.tra.2020.01.017

13. Andersson, A., Hiselius, L. W., & Adell, E. (2018). Promoting sustainable travel behaviour through the use of smartphone applications: A review and development of a conceptual model. Travel behaviour and society11, 52-61. doi:10.1016/j.tbs.2017.12.008. (in English) https://doi.org/10.1016/j.tbs.2017.12.008

14. Dolya, V. K., Gricyuk, P. M., Kristopchuk, M. E. (2006) "Investigation of the transport network of the region by the method of constructing the population density function", Journal of  Municipal Services of Cities, Tekhnіka Publisher, Volume 69, 205–211. (in Ukrainian)

15. Sivakumar, A. (2007). Modelling transport: a synthesis of transport modelling methodologies. Imperial College of London. (in English)

16. Hunt, J. D., & Simmonds, D. C. (1993). Theory and application of an integrated land-use and transport modelling framework. Environment and Planning B: Planning and DesignVolume 20(2), 221-244. (in English) https://doi.org/10.1068/b200221

17. Hunt, J. D., Kriger, D. S., & Miller, E. J. (2005). Current operational urban land‐use–transport modelling frameworks: A review. Transport reviewsVolume 25(3), 329-376. (in English) https://doi.org/10.1080/0144164052000336470

18. Krystopchuk, M. Ye. (2012) "Social and economic efficiency of passenger transportation system suburban communication", Monograph. NUWEE, Rivne, Ukraine. (in Ukrainian).

19. Profillidis, V. A., & Botzoris, G. N. (2018). Modeling of transport demand: Analyzing, calculating, and forecasting transport demand. Elsevier. (in English) https://doi.org/10.1016/B978-0-12-811513-8.00003-0

20. Antwi, T., Quaye-Ballard, J. A., Arko-Adjei, A., Osei-wusu, W., & Quaye-Ballard, N. L. (2020). Comparing Spatial Accessibility and Travel Time Prediction to Commercial Centres by Private and Public Transport: A Case Study of Oforikrom District. Journal of Advanced Transportation2020. doi:10.1155/2020/8319089. (in English) https://doi.org/10.1155/2020/8319089