Article 2 # 2’2020

DOI: 10.33868/0365-8392-2020-2-262-8-15
© Liliya Savchenko, Candidate of Technical Sciences (PhD), Associate Professor, Associate Professor of the Logistics Department, e-mail: lidia_savchenko@ukr.net, ORCID: 0000-0003-3581-6942;
© Andrii Donets, Candidate of Physical and Mathematical Sciences (PhD), Associate Professor, Associate Professor of the Logistics Department, e-mail: ogurman72@gmail.com, ORCID: 0000-0002-8122-051X (National Aviation University)

ASSESSMENT OF SOCIETY GENERAL ECONOMIC LOSSES BECAUSE OF TRAFFIC JAMS IN KIEV

Abstract. The problem of urban congestion is a constant challenge for various stakeholders in urban logistics are the city authorities, shippers, carriers and logistics companies, warehouse operators and direct recipients (shops, offices and residents). Road congestion is a source of increased air pollution, as well as direct losses of time and money. Thus, problems arising from congestion relate to any resident of the city and are more related to social issues. However, any social losses can be estimated in financial units. To estimate losses from urban congestion, the technology had been used that is widely spread in Europe to estimate external costs from transport. It is shown that these losses are significant for Kyiv, which in 2019 occupied 12th place in the world in terms of traffic congestion.
As you can see, the last mile logistics operators have to constantly look for ways to reduce the impact of road congestion on their transport and service flows. Current technologies offer, in particular, a shift in the delivery time for off-peak periods as well as for night hours. However, it is possible for a limited number of orders in last mile logistics. Thus, the rest are forced to face road congestion problems every day.
The paper considers various alternatives to urban delivery – car, motorcycle and bicycle. For these three options, a rating has been compiled showing the priority of a logistics tool of the last mile in terms of losses from road congestion. Such losses are determined for 2019, taking into account the composition of the traffic flow in Kyiv, the average delivery distance, as well as the different behavior of vehicles in traffic congestion. As a result, it was found that one passenger car delivering light parcels in the daytime predetermines congestion costs 3.3 times greater than a motorcycle and 12.5 times greater than a bicycle.
Keywords: city logistics, last mile logistics, city traffic jams, congestion costs, automobile delivery, motorcycle delivery, bicycle delivery.

References
1. Traffic Index. (2019). Tomtom. Retrieved from https://www.tomtom.com/en_gb/traffic-index/ranking/
2. Haubold, H. (2016). Cycling and congestion charges: a winning team for cities. European Cyclists’ Federation. Retrieved from https://ecf.com/groups/congestion-charges-and-cycling.
3. European Commission (2013) A call for smarter urban vehicle access regulations. Retrieved from https://ec.europa.eu/transport/sites/transport/files/themes/urban/doc/ump/swd%282013%29526-communication.pdf
4. Handbook on the External Costs of Transport, HECT (2019). Retrieved from https://ec.europa.eu/transport/sites/transport/files/studies/internalisation-handbook-isbn-978-92-79-96917-1.pdf.
5. Asaithambi G., Mourie H.S., Sivanandan R. (2017). Passenger Car Unit Estimation at Signalized Intersection for Non-lane Based Mixed Traffic Using Microscopic Simulation Model. Periodica Polytechnica Transportation Engineering 45(1): 12-20. DOI: 10.3311/PPtr.8986
6. Biswas, P., Bhattacharya, T., Chanda, A., Das, S., Hazra, S. (2018). Urban Wetlands – CO2 sink or source? A case study on the aquaculture ponds of East Kolkata Wetlands. International Journal of Recent Scientific Research. vol. 9, no. 2, 24158-24165. DOI: 10.24327/ijrsr.2018.0902.1608
7. Giuffrè O., Grana A., Giuffrè T., Acuto F. (2019). Passenger Car Equivalents for Heavy Vehicles at Roundabouts. А Synthesis Review. Frontiers in Built Environment 5. DOI: 10.3389/fbuil.2019.00080
8. Kanga N., Nakamura H. (2017). An Analysis of Characteristics of Heavy Vehicle Behavior at Roundabouts in Japan. Transportation Research Procedia. 25, 1485-1493. https://doi.org/10.1016/j.trpro.2017.05.176.
9. Sugiarto, S., Apriandy, F., Faisal, R., and Saleh, S. M. (2018). Measuring passenger car unit at four-legged roundabout using time occupancy data collected from drone. Aceh Int. J. Sci. Technol. 7, 77–84. doi: 10.13170/aijst.7.2.8587.
10. Srikanth, S., and Mehar, A. (2018). Development of MLR, ANN and ANFIS Models for estimation of PCUs at different levels of service. J. Soft Comput. Civil Eng. 2–1, 18–35. doi: 10.22115/SCCE.2018.50036
11. Zhou, J., Rilett, L., Jones, E., and Chen, Y. (2018). Estimating passenger car equivalents on level freeway segments experiencing high truck percentages and differential average speeds. J. Trans. Res. Board 2672, 44–54. doi: 10.1177/0361198118798237.
12. Yperman, I. (2011). Commuting by motorcycle: impact analysis, Transport & Mobility Leuven. Belgium. Report 10, 69.
13. Raj P., Sivagnanasundaram K., Asaithambi G., Ravi Shankar, A.U. (2019). Review of Methods for Estimation of Passenger Car Unit Values of Vehicles. Transportation engineering journal of ASCE. 145. DOI: 10.1061/JTEPBS.0000234.
14. Chandra S., Kumar U. (2003), Effect of Lane Width on Capacity under Mixed Traffic Conditions in India. Journal of Transportation Engineering 129(2). DOI: 10.1061/(ASCE)0733-947X(2003)129:2(155).
15. Salter R.J. (2016). Highway Traffic Analysis and Design. Macmillan International Higher Education. 378 р.
16. Pidrakhunok velosypedystiv. 2019. Retrieved from https://u-cycle.org.ua/projects/pidrakhunok-velosypedystiv/
17. Informatsiyno-analitychna systema “Mayno” (IAS «Mayno»). Retrieved from https://gis.kievcity.gov.ua/map/transport#map
18. Savchenko L.V. & Donets’ A.H. (2020). Porivnyannya vytrat vid avariynosti riznykh zasobiv mis’koyi dostavky u m. Kyyevi. Modelyuvannya ta informatsiyni systemy v ekonomitsi, 99, 24-34.
19. Cost of Living Comparison in 2020. (2020). Salary Explorer. http://www.salaryexplorer.com/cost-of-living-comparison.php
20. Serednia zarobitna plata v misti Kyievi vyshcha znachennia v Ukraini v 1,5 razy. (2019). Ofitsiinyi portal Kyieva. Retrieved from https://kyivcity.gov.ua/news/serednya_zarobitna_plata_v_misti_kiyevi_vischa_znachennya_v_ukrani_v_15_razi/