The need for eco-driving technologies in urban public transport

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dc.citation.epage82
dc.citation.issue1
dc.citation.spage73
dc.contributor.affiliationLutsk National Technical University
dc.contributor.authorSlatov, Ivan
dc.contributor.authorMurovany, Igor
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-07-05T07:55:32Z
dc.date.available2023-07-05T07:55:32Z
dc.date.created2023-06-30
dc.date.issued2023-06-30
dc.description.abstractРозглянуто виклики, що стоять перед громадським транспортом в Україні з точки зору скорочення споживання палива та викидів шкідливих речовин. Відсутність або недостатній розвиток засобів і методів моніторингу поведінки водіїв, а також висока плинність кадрів створюють значні труднощі в контролі за водіям та транспортними засобами. Проведене дослідження в Луцьку дало змогу проаналізувати поведінку водіїв пасажирських автобусів у місті. Результати показали, що типовими режимами водіння є холостий хід (40 %), прискорення (18 %), рух з постійною швидкістю (29 %) та гальмування (13 %). Дослідження також виявило середні значення прискорень і гальмувань, і ці результати не відповідають вимогам економного водіння. Встановлено кореляцію між поведінкою водія та цими динамічними характеристиками розгону і гальмування. Для вирішення зазначиних проблем запропоновано впровадження сучасних рішень, таких як системи допомоги за економного водіння (EDAS) або інтегровані системи, такі як FleetControl від TRIONA, які можуть допомогти проаналізувати умови експлуатації та зменшити витрату палива і викиди шкідливих речовин. Ці програми також можуть слугувати ефективними інструментами моніторингу як для окремих водіїв, так і для транспортних компаній. Описано ці програми та зроблено огляд досліджень, пов’язаних із їх використанням і розвитком. Крім того, наголошено на важливості навчання водіїв екологічному водінню як ефективного методу підвищення економічності використання палива в транспортних компаніях. Наголошено на необхідності подальших досліджень для повного розуміння складнощів функціонування громадського транспорту в Україні та потенційних переваг впровадження інноваційних технологій для сталого та ефективного майбутнього галузі.
dc.description.abstractThis article discusses the challenges facing public transport in Ukraine in terms of reducing fuel consumption and emissions. The absence or insufficient development of means and methods for monitoring driver behaviour, as well as high staff turnover, create significant difficulties in controlling drivers and vehicles. A conducted study in Lutsk, the administrative center of the Volyn region, analyzed the driving behavior of passenger buses in the city. Results showed that typical driving modes include idling (40 %), acceleration (18 %), driving at a constant speed (29 %), and braking (13 %). The study also revealed average accelerations and decelerations, and these results do not meet the requirements of ecological driving. The correlation between driver behavior and these dynamic acceleration and braking characteristics has been established. Possible causes for this phenomenon are discussed in the study. The article proposes the introduction of modern solutions to solve these problems. These solutions are Eco-Driving Assistance Systems (EDAS) or integrated systems, such as FleetControl from TRIONA, which can help learning operating conditions and reduce fuel consumption and emissions. These programmes can also serve as effective monitoring tools for individual drivers and transport companies. This paper describes these applications and reviews the research related to their use and development. In addition, the article highlights the importance of training drivers in eco-driving as a cost-effective method of improving fuel efficiency in transport companies. The paper concludes by emphasising the need for further research to fully understand the complexities of public transport in Ukraine and the potential benefits of introducing innovative technologies for a more sustainable and efficient future for the industry.
dc.format.extent73-82
dc.format.pages10
dc.identifier.citationSlatov I. The need for eco-driving technologies in urban public transport / Ivan Slatov, Igor Murovany // Transport Technologies. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 4. — No 1. — P. 73–82.
dc.identifier.citationenSlatov I., Murovany I. (2023) The need for eco-driving technologies in urban public transport. Transport Technologies (Lviv), vol. 4, no 1, pp. 73-82.
dc.identifier.doihttps://doi.org/10.23939/tt2023.01.073
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/59387
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofTransport Technologies, 1 (4), 2023
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dc.relation.references2. Ma, H., Xie, H., & Brown, D. (2017). Eco-driving assistance system for a manual transmission bus based on machine learning. IEEE Transactions on Intelligent Transportation Systems, 19(2), 572–581. doi: 10.1109/TITS.2017.2775633 (in English).
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dc.relation.referencesen2. Ma, H., Xie, H., & Brown, D. (2017). Eco-driving assistance system for a manual transmission bus based on machine learning. IEEE Transactions on Intelligent Transportation Systems, 19(2), 572–581. doi: 10.1109/TITS.2017.2775633 (in English).
dc.relation.referencesen3. Xiong, S., Xie, H., & Tong, Q. (2018). The effects of an eco-driving assistance system for a city bus on driving style. IFAC-PapersOnLine, 51(31), 331–336. doi: 10.1016/j.ifacol.2018.10.069 (in English).
dc.relation.referencesen4. Machine learning algorithm. Retrieved from: https://www.techtarget.com/whatis/definition/machinelearning-algorithm (in English).
dc.relation.referencesen5. Xu, N., Li, X., Liu, Q., & Zhao, D. (2021). An overview of eco-driving theory, capability evaluation, and training applications. Sensors, 21(19), 6547. doi: 10.3390/s21196547 (in English).
dc.relation.referencesen6. ECOdrive Connected. Retrieved from: https://www.ecodrive.eu/en/product/ecodrive-connected (in English).
dc.relation.referencesen7. Ping, P., Qin, W., Xu, Y., Miyajima, C., & Takeda, K. (2019). Impact of driver behavior on fuel consumption: Classification, evaluation and prediction using machine learning. IEEE access, 7, 78515–78532. doi: 10.1109/ACCESS.2019.2920489 (in English).
dc.relation.referencesen8. Almeida, J., & Ferreira, J. (2013). BUS public transportation system fuel efficiency patterns. In 2nd International conference on Machine Learning and computer Science (IMLcS'2013), (pp. 1–5). (in English).
dc.relation.referencesen9. Akena, R. p'O. (2014). Improving road transport energy efficiency through driver training. PhD thesis. University of Birmingham. Retrieved from: http://etheses.bham.ac.uk/id/eprint/5275 (in English).
dc.relation.referencesen10. Sullman, M. J., Dorn, L., & Niemi, P. (2015). Eco-driving training of professional bus drivers – Does it work?. Transportation Research Part C: Emerging Technologies, 58, 749–759. doi: 10.1016/j.trc.2015.04.010 (in English).
dc.relation.referencesen11. Ueki, S. and Takada, Y. (2011) Improvement of fuel economy and CO2 reduction of commercial vehicles by the promotion of Eco-Driving Management System (EMS), SAE Technical Paper Series [Preprint]. doi: 10.4271/2011-28-0048. (in English).
dc.relation.referencesen12. Scania develops fuel-saving driver support system for award-winning long-haul trucks. Retrieved from: https://www.mathworks.com/company/user_stories/scania-develops-fuel-saving-driver-support-system-for-awardwinning-long-haulage-trucks.html (in English).
dc.relation.referencesen13. Fleetcontrol. Retrieved from: https://www.triona.eu/products_services/products/fleetcontrol/ (in English).
dc.relation.referencesen14. Eco-drive for electric buses in coach traffic. Retrieved from: https://www.triona.eu/news/2022/eco-drivefor-electric-buses-in-coach-traffic/ (in English).
dc.relation.referencesen15. Sitovskyi, O. P., Dembitskyi, V. M., Mazyliuk, P. V., & Medviediev, I. I. (2018). Otsinka palyvnoi ekonomichnosti miskykh avtobusiv u yizdovomi tsykli pryvedenomu do realnykh umov rukhu [Evaluation fuel economy of city buses in the urbandriving cycle, adjusted to actual traffic conditions]. Suchasni tekhnolohii v mashynobuduvanni ta transporti [Advances in mechanical engineering and transport], 1(10), 112–116. (in Ukrainian).
dc.relation.urihttps://www.techtarget.com/whatis/definition/machinelearning-algorithm
dc.relation.urihttps://www.ecodrive.eu/en/product/ecodrive-connected
dc.relation.urihttp://etheses.bham.ac.uk/id/eprint/5275
dc.relation.urihttps://www.mathworks.com/company/user_stories/scania-develops-fuel-saving-driver-support-system-for-awardwinning-long-haulage-trucks.html
dc.relation.urihttps://www.triona.eu/products_services/products/fleetcontrol/
dc.relation.urihttps://www.triona.eu/news/2022/eco-drivefor-electric-buses-in-coach-traffic/
dc.rights.holder© Національний університет „Львівська політехніка“, 2023
dc.rights.holder© I. Slatov, I. Murovanyi, 2023
dc.subjectповедінка водія
dc.subjectекологічне водіння
dc.subjectпаливна ефективність
dc.subjectгромадський транспорт
dc.subjectмоніторинг в реальному часі
dc.subjectміський транспорт
dc.subjectексплуатація транспортних засобів
dc.subjectексплуатаційні витрати
dc.subjectсталий транспорт
dc.subjectуправління автопарком
dc.subjectоптимізація алгоритмів
dc.subjectвплив на навколишнє середовище
dc.subjectdriver behavior
dc.subjecteco-driving
dc.subjectfuel efficiency
dc.subjectpublic transport
dc.subjectreal-time monitoring
dc.subjecturban transport
dc.subjectvehicle operation
dc.subjectoperating costs
dc.subjectsustainable transportation
dc.subjectfleet management
dc.subjectalgorithm optimization
dc.subjectenvironmental impact
dc.titleThe need for eco-driving technologies in urban public transport
dc.title.alternativeПотреба впровадження технологій екологічного водіння в міському громадському транспорті
dc.typeArticle

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Transport Technologies. – 2023. – Vol. 4, No. 1