Optimization of Vehicle Operating Conditions by Using Simulation Modeling Software
Published January 16, 2019 by SAE International in United States
Downloadable datasets for this paper availableAnnotation of this paper is available
The paper describes the process of modeling and optimizing the operating conditions of vehicles for a section of the transport network using simulation tools. The cyphergrams of the transport flow intensities in the transportation hub were built, a graphic model of vehicle traffic in the transportation hub was built, and a transition probability matrix was compiled, which was used to simulate modeling and optimize vehicle operating conditions for the considered transport hub. It is necessary to use simulation modeling software that supports all simulation methods and a powerful built-in library for traffic modeling. The corresponding simulation model was created. With the help of it, modeling in the transport hub selected for research has been carried out and the optimum values of the duration of the phases of traffic light objects have been obtained. It has reduced the average travel time through the site, which is considered in the work, and the number of cars in traffic jams. In the process of modeling, the objective function is formed with the corresponding restrictions. Also, the task of optimizing operating conditions in the transport hub under study is formulated. Different process diagrams of the simulation model were created for different input parameters. Relevant agents and their populations were created too. The simulation error was 4%, which confirms the feasibility of using selected simulation modeling software to simulate and optimize the operating conditions of vehicles. In the future, modeling of a set of network sections can be used to select the optimal route for a vehicle, based on the optimization problem. The model can be used to solve problems of optimizing the movement of vehicles, and can also be used in the simulation and operation of intelligent transport systems in operating conditions.
- Mykyta Volodarets - Ukrainian State Univ. of Railway Transp
- Igor Gritsuk - Kherson State Maritime Academy
- Nataliia Chygyryk - Ukrainian State Univ. of Railway Transp
- Evgen Belousov - Kherson State Maritime Academy
- Andrii Golovan - Odessa National Maritime University
- Olena Volska - Kherson State Agrarian University
- Vitalii Hlushchenko PhD - National Academy of Nat. Guard of Ukr.
- Dmytro Pohorletskyi - Kherson State Maritime Academy
- Olga Volodarets - Ukrainian State Univ. of Railway Transp.
CitationVolodarets, M., Gritsuk, I., Chygyryk, N., Belousov, E. et al., "Optimization of Vehicle Operating Conditions by Using Simulation Modeling Software," SAE Technical Paper 2019-01-0099, 2019, https://doi.org/10.4271/2019-01-0099.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
|[Unnamed Dataset 3]|
|[Unnamed Dataset 4]|
|[Unnamed Dataset 5]|
|[Unnamed Dataset 6]|
|[Unnamed Dataset 7]|
- Surface Transportation Policy Project, “An Analysis of the Relationship between Highway Expansion and Congestion in Metropolitan Areas,” Lessons from the 15-Year Texas Transportation Institute Study, November 1998.
- Kiselev, A.B., Kokoreva, A.V., Nikitin, V.F., and Smirnov, N.N., “Mathematical Modeling of Traffic Flow on Controlled Roads,” Journal of Applied Mathematics and Mechanics 68:933-939, 2004, doi:10.1016/j.jappmathmech.2004.11.014.
- Allsop, R., “Some Reflections on Forty Years’ Evolution of Transport Studies,” in 38th Annual Conference of the Universities Transport Study Group, Dublin, January 2006.
- Županović, D., Anžek, M., and Kos, G., “Optimisation of Signal Controlled Intersection Capacity,” Promet - Traffic -Traffico 22(6):419-431, 2010, doi:10.7307/ptt.v22i6.207.
- Khastgir, S., Dhadyalla, G., Birrell, S., Redmond, S. et al., “Test Scenario Generation for Driving Simulators Using Constrained Randomization Technique,” SAE Technical Paper 2017-01-1672, 2017, doi:10.4271/2017-01-1672.
- Xu, Z., “Macroscopic Traffic States Estimation Based on Vehicle-to-Infrastructure (V2I) Connected Vehicle Data,” SAE Technical Paper 2017-01-2013, 2017, doi:10.4271/2017-01-2013.
- Guseynov, S. and Berezhnoy, A., “Modelling of Urban Traffic Flow,” Environment. Technology. Resources, Proceedings of the International Scientific and Practical Conference 1:109-114, 2017, doi:10.17770/etr2017vol1.2632.
- Li, J., Wu, J., Sun, H., Jiang, Y. et al., “Traffic Modeling Considering Motion Uncertainties,” SAE Technical Paper 2017-01-2000, 2017, doi:10.4271/2017-01-2000.
- Kim, N., Karbowski, D., and Rousseau, A., “A Modeling Framework for Connectivity and Automation Co-Simulation,” SAE Technical Paper 2018-01-0607, 2018, doi:10.4271/2018-01-0607.
- Kerner, B.S., Introduction to Modern Traffic Flow Theory and Control: The Long Road to Thre (Springer, 2009).
- Daganzo, C.F., Fundamentals of Transportation and Traffic Operations (New York: Pergamon Press, 1997).
- Hensher, D.A. and Button, K.J., Handbook of Transport Modelling (London, United Kingdom: Pergamon Press, 2000).
- Banks, J., Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice (John Wiley & Sons, 1998).
- Govorushchenko, N.Ya. and Turenko, A.N., “Transport Systems Engineering (on the Example of Automobile Transport),” Part 1, Kharkov, RIO KhGADTU, 1998.
- Govorushchenko, N.Ya. and Turenko, A.N., “Systems Engineering and Design of Transport Machines,” Kharkov, HNADU, 2004.
- Volodarets, M., Kletska, O., Hatchenko, V., Shuleshko, D., and Kosariev, O., “Determination Parameters of a Hybrid Vehicle in Its Life Cycle,” International Journal of Engineering & Technology 7(4.3):339-343, 2018, doi:10.14419/ijet.v7i4.3.19830.
- Gorobchenko, O., Fomin, O., Gritsuk, I., Saravas, V., Grytsuk, Yu., Bulgakov, M., Volodarets, M., and Zinchenko, D., “Intelligent Locomotive Decision Support System Structure Development and Operation Quality Assessment,” in 2018 IEEE 3rd International Conference on Intelligent Energy and Power Systems (IEPS), Kharkiv, 2018, 239-243, doi:10.1109/IEPS.2018.8559487.
- Kuric, I., Mateichyk, V., Smieszek, M., Tsiuman, M., Goridko, N. and Gritsuk, I., “The Peculiarities of Monitoring Road Vehicle Performance and Environmental Impact,” in Innovative Technologies in Engineering Production (ITEP’18), MATEC Web of Conferences 244, 03003, 2018, doi:10.1051/matecconf/201824403003.
- Gritsuk, I., Volkov, V., Mateichyk, V., Grytsuk, Y. et al., “Information Model of V2I System of the Vehicle Technical Condition Remote Monitoring and Control in Operation Conditions,” SAE Technical Paper 2018-01-0024, 2018, doi:10.4271/2018-01-0024.
- Gritsuk, I., Volkov, V., Mateichyk, V., Gutarevych, Y. et al., “The Evaluation of Vehicle Fuel Consumption and Harmful Emission Using the Heating System in a Driving Cycle,” SAE Int. J. Fuels Lubr. 10(1):236-248, 2017, doi:10.4271/2017-26-0364.
- Klets, D., Gritsuk, I., Makovetskyi, A., Bulgakov, N. et al., “Information Security Risk Management of Vehicles,” SAE Technical Paper 2018-01-0015, 2018, doi:10.4271/2018-01-0015.
- Vychuzhanin, V., Rudnichenko, N., Shybaiev, D., Gritsuk, I. et al., “Cognitive Model of the Internal Combustion Engine,” SAE Technical Paper 2018-01-1738, 2018, doi:10.4271/2018-01-1738.
- Hahanov, V., Gharibi, W., Litvinova, E., Chumachenko, S. et al., “Cloud-Driven Traffic Monitoring and Control Based on Smart Virtual Infrastructure,” SAE Technical Paper 2017-01-0092, 2017, doi:10.4271/2017-01-0092.
- Semenov, V.V. and Yermakov, A.V., “Historical Analysis of the Modeling of Transport Processes and Transport Infrastructure,” Preprint of the Keldysh IPM, 3, 2015.