SEARCH WITHIN CONTENT
Citation Information : Transport Problems. Volume 16, Issue 3, Pages 29-40, DOI: https://doi.org/10.21307/tp-2021-039
License : (CC BY 4.0)
Received Date : 12-April-2020 / Accepted: 07-September-2021 / Published Online: 30-September-2021
This article focuses on traffic modeling of intersections in Aimsun. The intersections studied are in Bratislava, the capital of Slovakia. Every year, the number of vehicles on roads increases and congestions are created. Individual intersections do not have unlimited capacity. Simulations help to predict possible future problems and thus the possibility to prevent them. Accordingly, at intersections on Vajnorská street, a traffic survey was carried out using video cameras. Then, simulations were carried out in Aimsun. The results are shown in the tables separately for each intersection along with the determined overall quality level of the intersection. In addition to the current situation, simulations were carried out for increased traffic by 10% and 20%, and overall quality levels were also determined. Finally, the results were evaluated and compared with each other. This article points out the importance of research into the permeability of important points of the road network: intersections. It is necessary to carry out capacity assessments when planning any construction that will affect traffic in each location.
1. Šarkan, B. & Caban, J. & Marczuk, A. & Vrábel, J. & Gnap, J. Composition of exhaust gases of spark ignition engines under conditions of periodic inspection of vehicles in Slovakia. Przemysl Chemiczny. 2017. T. 96. Nr 3. P. 675-680.
2. The total number of registered vehicles in the Slovak Republic. Available at: https://www.minv.sk/?celkovy-pocet-evidovanych-vozidiel-v-sr.
3. Das, B. & Boral, E. Assessment of the road characteristics of selected north-south and east-west aligned roads within Agartala Municipal Corporation. Tripura, India. Current Science. 2020. Vol. 119. Issue 1. P. 112-118. DOI: 10.18520/cs/v119/i1/.
4. Schrank, D. & Lomax, T. & Turner, S. Urban mobility report Texas Transportation Institute. Texas: Texas Transportation Institute. 2020.
5. Anbaroglu, B. & Heydecker, B.G. & Cheng, T. Spatio-temporal clustering for non-recurrent traffic congestion detection on urban road networks. Transportation Research Part C-emerging Technologies, 2013. Vol. 48. P. 47-65.
6. Anbaroğlu, B. & Cheng, T. & Heydecker, B. Non-recurrent traffic congestion detection on heterogeneous urban road networks. Transportmetrica A: Transport Science, 2015. Vol. 11. Issue 9. P. 754-771. DOI: 10.1080/23249935.2015.1087229.
7. Chung, Y. Assessment of non-recurrent traffic congestion caused by freeway work zones and its statistical analysis with unobserved heterogeneity. Transport Policy. 2011. Vol. 18. No. 4. P. 587-594.
8. Zheng, Z. & Wang, Z. & Zhu, L. & Jiang, H. Determinants of the congestion caused by a traffic accident in urban road networks. Accident; analysis and prevention. 2019. Vol. 136. DOI: 10.1016/j.aap.2019.105327.
9. Bai, Q. & Gao, Z. & Qu, Z. & Tao, Ch. Modeling for Left-Lane Line Extensions at Signalized Intersections with Permitted Left-Turning Phase. Journal of Transportation Engineering, Part A: Systems. 2020. Vol. 146. No. 8. DOI: https://doi.org/10.1061/JTEPBS.0000404.
10. Karoń, G. & Mikulski, J. Transportation Systems Modelling as Planning, Organisation and Management for Solutions Created with ITS. In: Mikulski J. (eds) Modern Transport Telematics. 2011. P. 277-290. DOI: 10.1007/978-3-642-24660-9_32.
11. Astarita, V. & Festa, D.C. & Giofrè, V.P. & Guido, G. Surrogate safety measures from traffic simulation models a comparison of different models for intersection safety evaluation. Transportation Research Procedia. 2019. Vol. 37. P. 219-226. DOI: 10.1016/j.trpro.2018.12.186.
12. Terentyev, V. & Andreev, K. & Anikin, N. & Morozova, N. & Shemyakin, A. The use of simulation when designing road junctions. In: E3S Web of Conferences. 2020. DOI: 10.1051/e3sconf/202016403042.
13. Čulík, K. & Harantová, V. & Kalašová, A. Traffic Modelling of the Circular Junction in the City of Žilina. Advances in Science and Technology. Research Journal. 2019. Vol. 13(4). P. 162-169.
14. Fedorko, G. & Molnár, V. & Strohmandl, J. & Vasil, M. Development of simulation model for light-controlled road junction in the program Technomatix Plant Simulation. Transport Means – Proceedings of the International Conference. 2015. P. 466-469. ISSN: 1822-296X.
15. Zhao, J. & Knoop, V.L. & Wang, M. Two-dimensional vehicular movement modelling at intersections based on optimal control. Transportation Research Part B: Methodological. 2020. Vol. 138. P. 1-22.
16. Ostrowski, K. & Budzynski, M. Modelling Signalised Intersections Reliability of Functioning. IOP Conference Series: Materials Science and Engineering. 2019. Vol. 471(6): 062028. DOI: 10.1088/1757-899X/471/6/062028.
17. Xu, D. & Wang, Y. & Peng, P. & Beilun, S. & Deng, Z. & Guo, H. Real-time road traffic state prediction based on Kernel-KNN. In: Transportmetrica A: Transport Science. 2018. Vol. 16. Issue 1. P. 1-23. DOI: 10.1080/23249935.2018.1491073.