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Enhancing driving cycle development using artificial intelligence
1
Faculty of Automotive and Construction Machinery Engineering, Warsaw University of Technology, Poland
These authors had equal contribution to this work
Submission date: 2025-06-15
Final revision date: 2025-08-09
Acceptance date: 2025-08-25
Online publication date: 2025-09-14
Publication date: 2025-11-14
Corresponding author
Jakub Lasocki
Faculty of Automotive and Construction Machinery Engineering, Warsaw University of Technology, Narbutta 84, 02-524, Warszawa, Poland
Faculty of Automotive and Construction Machinery Engineering, Warsaw University of Technology, Narbutta 84, 02-524, Warszawa, Poland
Combustion Engines 2025,203(4), 146-154
KEYWORDS
TOPICS
ABSTRACT
In recent years, artificial intelligence (AI) has found application in numerous technical areas, including the automotive research and development sector. This paper considers the use of AI tools for the development of driving cycles for testing vehicles on a chassis dynamometer. The above idea was investigated on the example of a driving cycle simulating the use of a passenger car in urban conditions. The empirical data were collected during vehicle road tests in real traffic and then processed statistically by determining the values of selected driving pattern characteristics. Sections of vehicle velocity courses (‘micro-trips’) were selected and combined into a driving cycle representative of the road conditions prevailing during road tests. Processing of empirical data and combining velocity sections into a driving cycle was performed using AI-enhanced software utilizing large language models that convert user commands in natural language into Python code. The developed driving cycle was compared with selected standard urban driving cycles in terms of the values of driving pattern characteristics.
REFERENCES (33)
1.
Adamiak B, Andrych-Zalewska M, Merkisz J, Chłopek Z. The uniqueness of pollutant emission and fuel consumption test results for road vehicles tested on a chassis dynamometer. Eksploat Niezawodn. 2025;27(1):195747. https://doi.org/10.17531/ein/1....
2.
Andrych-Zalewska M, Chłopek Z, Merkisz J, Pielecha J. Determination of characteristics of pollutant emission from a vehicle engine under traffic conditions in the engine test. Combustion Engines. 2022;191(4):58-65. https://doi.org/10.19206/CE-14....
3.
Barlow T, Latham S, McCrae I, Boulter P. A reference book of driving cycles for use in the measurement of road vehicle emissions. Wokingham (UK): Transport Research Laboratory; 2009. (TRL Published Project Report). https://assets.publishing.serv....
4.
Boulter PG, Barlow TJ, McCrae IS, Latham S, Parkin C. Emission factors 2009: report 1 – a review of methods for determining hot exhaust emission factors for road vehicles. Crowthorne (UK): Transport Research Laboratory; 2009. PPR353. https://assets.publishing.serv....
5.
Brady J, O’Mahony M. Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas. Appl Energy. 2016;177:165-178. https://doi.org/10.1016/j.apen....
6.
Chłopek Z, Biedrzycki J, Lasocki J, Wójcik P. Correlational analysis of pollutant emission intensity in various conditions of operation of the automotive internal combustion engine. Transport. 2019;34:490-498. https://doi.org/10.3846/transp....
7.
Chłopek Z, Lasocki J. Zerowymiarowe charakterystyki testów jezdnych do celów modelowania emisji zanieczyszczeń z samochodowych silników spalinowych (in Polish). Przem Chem. 2024;103:1465-1468. https://doi.org/10.15199/62.20....
8.
Galgamuwa U, Perera L, Bandara S. Developing a general methodology for driving cycle construction: comparison of various established driving cycles in the world to propose a general approach. J Transp Technol. 2015;5:191-203. https://un.uobasrah.edu.iq/dow....
9.
Gebisa A, Gebresenbet G, Gopal R, Nallamothu RB. Driving cycles for estimating vehicle emission levels and energy consumption. Future Transp. 2021;1(3):615-638. https://doi.org/10.3390/future....
10.
Gebisa A, Gebresenbet G, Gopal R, Nallamothu RB. A neural network and principal component analysis approach to develop a real-time driving cycle in an urban environment: the case of Addis Ababa, Ethiopia. Sustainability. 2022;14(21):13772. https://doi.org/10.3390/su1421....
11.
Giakoumis EG. Driving and engine cycles. Athens: Springer; 2017. https://doi.org/doi:10.1007/97....
12.
Giraldo M, Quirama LF, Huertas JI, Tibaquirá JE. The effect of driving cycle duration on its representativeness. World Electr Veh J. 2021;12(4):212. https://doi.org/10.3390/wevj12....
13.
Gnap J, Šarkan B, Konečný V, Skrúcaný T. The impact of road transport on the environment. In: Sładkowski A (ed.). Ecology in transport: problems and solutions. Springer, Cham 2020. https://doi.org/10.1007/978-3-....
14.
Hassija V, Chamola V, Mahapatra A, Singal A, Goel D, Huang K et al. Interpreting black-box models: a review on explainable artificial intelligence. Cogn Comput. 2024;16:45-74. https://doi.org/10.1007/s12559....
15.
Hung WT, Tong HY, Lee CP, Ha K, Pao LY. Development of a practical driving cycle construction methodology: a case study in Hong Kong. Transp Res D Transp Environ. 2007;12:115-128. https://doi.org/10.1016/j.trd.....
16.
Huo J, Peng C. Depletion of natural resources and environmental quality: prospects of energy use, energy imports, and economic growth hindrances. Resour Policy. 2023;86:104049. https://doi.org/10.1016/j.reso....
17.
Jia X, Wang H, Xu L, Wang Q, Li H, Hu Z et al. Constructing representative driving cycle for heavy duty vehicle based on Markov chain method considering road slope. Energy AI. 2022;7:100123. https://doi.org/10.1016/j.egya....
18.
Julius. The AI data analyst that works for you [Internet]. San Francisco: Caesar Labs Inc; 2025. https://julius.ai/ (accessed on 2025.08.08).
19.
Lasocki J, Chłopek Z, Godlewski T. Driving style analysis based on information from the vehicle's OBD system. Combust Engines. 2019;178(3):173-181. https://doi.org/doi:10.19206/C....
20.
Lasocki J. The WLTC vs NEDC: a case study on the impacts of driving cycle on engine performance and fuel consumption. Int J Automot Mech Eng. 2021;18:9071-9081. https://journal.ump.edu.my/ija....
21.
Londoño J, Serna Cartagena JF, Gomez Miranda IN, Ruiz Holguin FA, Agudelo AF. Methodology for determining motorcycle driving cycles applying computational intelligence tools: case study of Medellín, Colombia. SSRN. https://doi.org/10.2139/ssrn.5....
22.
Lyu P, Wang P, Liu Y, Wang Y. Review of the studies on emission evaluation approaches for operating vehicles. J Traffic Transp Eng. 2021;8:493-509. https://doi.org/10.1016/j.jtte....
23.
Mostasharshahidi S, Salamat MK, Ghobadian B, Masih-Tehrani M. Agricultural tractor driving cycle extraction using artificial intelligence. J Eng Res. 2024;70(4):14-26. https://doi.org/10.22034/er.20....
24.
Orliński P, Gis M, Bednarski M, Novak N, Samoilenko D, Prokhorenko A. The legitimacy of using hybrid vehicles in urban conditions in relation to empirical studies in the WLTC cycle. Probl Ekspl. 2019;112:25-30. http://www.jmcm.itee.radom.pl/....
25.
Pielecha J, Kurtyka K. Exhaust emissions from Euro 6 vehicles in WLTC and RDE – part 1: methodology and similarity conditions studies. Energies. 2023;16:7465. https://doi.org/10.3390/en1622....
26.
Qiu D, Li Y, Qiao D. Recurrent neural network based driving cycle development for light duty vehicles in Beijing. Transp Res Procedia. 2018;34:147-154. https://doi.org/10.1016/j.trpr....
27.
Quirama LF, Giraldo M, Huertas JI, Tibaquirá JE, Cordero-Moreno D. Main characteristic parameters to describe driving patterns and construct driving cycles. Transp Res D Transp Environ. 2021;97:102959. https://doi.org/10.1016/j.trd.....
28.
Rivera-Campoverde ND, Arenas-Ramírez B, Muñoz Sanz JL, Jiménez E. GPS data and machine learning tools, a practical and cost-effective combination for estimating light vehicle emissions. Sensors. 2024;24(7):2304. https://doi.org/10.3390/s24072....
29.
Sankar SS, Xia Y, Carmai J, Koetniyom S. Optimal eco-driving cycles for conventional vehicles using a genetic algorithm. Energies. 2020;13(17):4362. https://doi.org/10.3390/en1317....
30.
Shi S, Lin N, Zhang Y, Cheng J, Huang C, Liu L et al. Research on Markov property analysis of driving cycles and its application. Transp Res D Transp Environ. 2016;47:171-181. https://doi.org/10.1016/j.trd.....
31.
Tong HY, Hung WT. A framework for developing driving cycles with on-road driving data. Transp Rev. 2010;30(5):589-615. https://doi.org/10.1080/014416....
32.
von Eschenbach WJ. Transparency and the black box problem: why we do not trust AI. Philos Technol. 2021;34:1607-1622. https://doi.org/10.1007/s13347....
33.
Zimakowska-Laskowska M, Kozłowski E, Laskowski P, Wiśniowski P, Świderski A, Orynycz O. Vehicle exhaust emissions in the light of modern research tools: synergy of chassis dynamometers and computational models. Combustion Engines. 2025;200(1):145-54. https://doi.org/10.19206/CE-20....
CITATIONS (1):
1.
Construction of slope-included energy consumption-representative driving cycle for heavy-duty commercial vehicles using multi-dimensional index parameter selection and adaptive crayfish-genetic algorithm
Degang Li, Haozhe Song, Miao Yang, Hao Zhang, Wanchen Sun, Liang Guo, Dawei Qu
Energy Conversion and Management
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