Joint Stock Company “Institute of Telecommunications
Russian Federation
Russian Federation
St. Petersburg, Russian Federation
Joint Stock Company “Institute of Telecommunications
Russian Federation
Objective: in order to improve safety, as well as optimize the path of movement in everyday life to reduce the time on the road, there are now more and more prerequisites for the introduction of highly automated and fully automated vehicles into various spheres of human life. This will optimize and improve the road system of the country as a whole, and most importantly — reduce accidents and, consequently, improve road safety. When implementing these vehicles, it is necessary to develop an algorithm for communication between different road users under different conditions and distances between objects. Methods: this study uses simulation modeling methods, the method of tabular and graphical data display, the method of factor analysis, methods of model experiment, as well as the method of expert assessments. Results: within the framework of the work, an algorithm has been developed for transmitting messages with different content and priority information between two highly automated / fully automated vehicles or a vehicle with an automated state infrastructure using various communication channels, as well as a simulation model based on it, which was created in the AnyLogic modeling environment. The use of different priorities allows you to guarantee the minimum delivery time of the most important messages containing information for vehicle management. As a result of the simulation, histograms of the probabilistic-temporal characteristics of the transmission of messages of various priorities and messages confirming their delivery were obtained using various communication channels. Practical significance: the simulation results make it possible to assess the quality and time of message delivery under specified conditions and to ensure effective transmission of information by changing the intensity and size of messages, the use of various communication channels and their speeds, and so on.
automation, vehicle, simulation modeling, communication channel, digitalization, automated vehicle, communication network
1. Mintrans Rossii razrabotal otraslevuyu Strategiyu cifrovoy transformacii [Elektronnyy resurs]. URL: https://mintrans.gov.ru/press-center/ news/9985 (data obrascheniya: 30.01.2023).
2. Takács Á., Rudas I., Bösl D., et al. Highly Automated Vehicles and Self-Driving Cars [Industry Tutorial] // IEEE Robotics & Automation Magazine. Dec. 2018. Vol. 25, no. 4. P. 106–112. DOI: 10.1109/ MRA.2018.2874301.
3. Vchera i zavtra: 6 urovney avtomatizacii avtomobiley [Elektronnyy resurs]. URL: https:// novate.ru/blogs/110617/41716/ (data obrascheniya: 25.03.2023).
4. GOST R 70249–2022. Sistemy iskusstvennogo intellekta na avtomobil'nom transporte. Vysokoavtomatizirovannye transportnye sredstva. Terminy i opredeleniya. M.: Rossiyskiy institut standartizacii, 2022. 16 s.
5. Rasporyazhenie Pravitel'stva RF ot 25.03.2020 № 724‑r «O Koncepcii obespecheniya bezopasnosti dorozhnogo dvizheniya s uchastiem bespilotnyh transportnyh sredstv na avtomobil'nyh dorogah obschego pol'zovaniya» [Elektronnyy resurs] URL: https://www.garant.ru/products/ipo/prime/doc/73707148/#:~:text=%22polnost'yu%20avtomatizirovannoe%20transportnoe%20sredstvo%22%20-,dorozhnogo%20dvizheniya%20(fully%20automated%20 vehicle) (data obrascheniya: 30.01.2023).
6. Malineckiy G. G., Semenov V. V. Dorozhnoe dvizhenie v kontekste fundamental'nyh issledovaniy. Preprint. Institut prikladnoy matematiki im. M. V. Keldysha (IPM RAN) № 64. M., 2007.
7. Komarov V. V. Ponyatiynyy apparat dlya opisaniya sistem avtomatizirovannogo vozhdeniya avtotransportnyh sredstv / V. V. Komarov, S. A. Garagan // Transport Rossiyskoy Federacii. Zhurnal o nauke, praktike, ekonomike. 2019. № 3 (82). S. 26–33.
8. Kulikova Ya. Scenarii upravleniya bespilotnymi transportnymi sredstvami v srede «Umnogo goroda» / Ya. Kulikova, D. Kachalov, M. P. O. Farhadov // Informacionnye tehnologii i matematicheskoe modelirovanie (ITMM‑2020): Materialy XIX Mezhdunarodnoy konferencii imeni A. F. Terpugova (2–5 dekabrya 2020 g.). Tomsk: Izd-vo NTL, 2021. S. 308–313.
9. Dadenkov S. A. Vybor sredy imitacionnogo modelirovaniya informacionno-upravlyayuschih setey / S. A. Dadenkov, E. L. Kon // Vestnik Permskogo universiteta. 2019. № 1 (44). S. 58–69.
10. Kupriyashkin A. G. Osnovy modelirovaniya sistem: ucheb. posobie. Noril'sk: Noril'skiy industr. in-t, 2015. 135 s.
