Safety aspects of critical scenario identification for autonomous transport

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Arpad Torok
Gábor Pauer


An important part of the definition of sustainability is safety. This study is based on the basic concept of connected transport systems. After defining the basic model, the research aims to simplify the models of highly automated transport systems that are suitable for safety assessment of critical scenarios, including various safety aspects. Accordingly, the basic safety requirements of autonomous systems responsible for the management of traffic processes are summarized. Based on the derived requirements, some of the most relevant safety indicators and the constraints of the simplification process are listed.

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Torok, A., & Pauer, G. (2022). Safety aspects of critical scenario identification for autonomous transport . Cognitive Sustainability, 1(1).


Daganzo, C. F. (1994). The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Research Part B: Methodological. 28(4), 269–287. DOI:

Daganzo, C. F. (1995). The cell transmission model, part II: Network traffic. Transportation Research Part B: Methodological. 29(2), 79–93. DOI:

Derenda, T., Zanne, M., Zoldy, M., Torok. A. (2018). Automatization in road transport: a review. Production Engineering Archives. 20(20), 3–7. DOI:

Dinh Van, N., Sualeh, M., Kim, D., Kim, G-W. (2020). A Hierarchical Control System for Autonomous Driving towards Urban Challenges. Applied Sciences. 10(10), 3543. DOI:

Földes, D., Csiszár, C., Tettamanti, T. (2021). Automation Levels of Mobility Services. Journal of Transportation Engineering, Part A: Systems. 147(5). DOI:

Fu, R., Li, Z., Sun, Q., Wang, C. (2019). Human-like car-following model for autonomous vehicles considering the cut-in behavior of other vehicles in mixed traffic. Accident Analysis & Prevention. 132, 105260. DOI:

Huang, C., Li, L. (2020). Architectural design and analysis of a steer-by-wire system in view of functional safety concept. Reliability Engineering & System Safety. 198, 106822. DOI:

Jima, D., Sipos, T. (2022). The Impact of Road Geometric Formation on Traffic Crash and Its Severity Level. Sustainability. 14(14), 8475. DOI:

Lengyel, H., Tettamanti, T., Szalay, Z. (2020). Conflicts of automated driving with conventional traffic infrastructure. IEEE Access. 8, 163280–163297. DOI:

Lo, H. K., Szeto, W. Y. (2002). A cell-based variational inequality formulation of the dynamic user optimal assignment problem. Transportation Research Part B: Methodological. 36(5), 421–443. DOI:

Messerli, R., Murniningtyas, E., Eloundou-Enyegue, P., Foli, E. G., Furman, E., Glassman, A., Hernandez Licona, G., Kim, E. M., Lutz, W., Moatti, J. P., Richardson, K., Saidam, M., Staniškis, J. K., Ypersele, J-P. V. (2019). Global Sustainable Development Report 2019: The Future is Now – Science for Achieving Sustainable Development. United Nations Publications. United Nations, New York, NY.

Mikusova, M. (2017). Crash avoidance systems and collision safety devices for vehicle occupants. MATEC Web of Conferences. 107, 00024. DOI:

Nyerges, Á., Szalay, Zs. (2017). A new approach for the testing and validation of connected and automated vehicles. 34th International Colloquium on Advanced Manufacturing and Repairing Technologies in Vehicle Industry. . 4, p111–114.

Pauer, G., Török, Á. (2019). Comparing System Optimum-based and User Decision-based Traffic Models in an Autonomous Transport System. Promet – Traffic&Transportation. 31(5), 581–591. DOI:

Pauer, G., Török, Á. (2021). Binary integer modeling of the traffic flow optimization problem, in the case of an autonomous transportation system. Operations Research Letters. 49(1), 136–143. DOI:

Pauer, G., Török, Á. (2022). Introducing a novel safety assessment method through the example of a reduced complexity binary integer autonomous transport model. Reliability Engineering & System Safety. 217, 108062. DOI:

Peeta, S., Ziliaskopoulos, A. (2001). Foundations of dynamic traffic assignment: the past, the present and the future. Networks and Spatial Economics. 1, 233–265. DOI:

Sipos, T., Afework Mekonnen, A., Szabó, Z. (2021). Spatial econometric analysis of road traffic crashes. Sustainability. 13(5), 2492. DOI:

Szabó, Z., Sipos, T. (2020). Separation effects in a microregion: traffic volume estimation between the settlements of Lake Velence. Regional Statistics. 10(2), 186–205. DOI:

Szalay, Z. (2021). Next generation X-in-the-loop validation methodology for automated vehicle systems. IEEE Access. 9, 35616–35632. DOI:

Szalay, Z., Nyerges, Á., Hamar, Z., Hesz, M. (2017). Technical specification methodology for an automotive proving ground dedicated to connected and automated vehicles. Periodica Polytechnica Transportation Engineering. 45(3), 168–174. DOI:

Szendrő, G., Csete, M., & Török, Á. (2014). The sectoral adaptive capacity index of Hungarian road transport. Periodica Polytechnica-Social and Management Sciences, 22(2), 99-106. DOI:

Szeto, W. Y., Lo, H. K. (2004). A cell-based simultaneous route and departure time choice model with elastic demand. Transportation Research Part B: Methodological. 38(7), 593–612.DOI:

Tampère, C. M. J., Corthout, R., Cattrysse, D., Immers, L. H. (2011). A generic class of first order node models for dynamic macroscopic simulation of traffic flows. Transportation Research Part B: Methodological. 45(1), 289–309.DOI:

Tettamanti, T., Varga, I., Szalay, Z. (2016). Impacts of autonomous cars from a traffic engineering perspective., Periodica Polytechnica Transportation Engineering. 44(4), 244–250. DOI:

Torok, A., Torok, A., & Heinitz, F. (2014). Usage of production functions in the comparative analysis of transport related fuel consumption. Transport and Telecommunication, 15(4), 292. DOI:

Török, Á. (2011). Investigation of road environment effects on choice of urban and interurban driving speed. International Journal for Traffic and Transport Engineering, 1(1), 1-9.

Török, Á. (2020). A novel methodological framework for testing automated vehicle functions. European Transport Research Review. 12(1), 1–9. DOI:

Yperman, I. (2007). The Link Transmission Model for dynamic network loading. Open Access Publ. from Kathol. Univ. Leuven, 2007. URL: (Downloaded: 4 Auguast 2022)

Yperman, I., Tampère, C.M.J., Immers, B. (2007). A Kinematic Wave Dynamic Network Loading Model Including Intersection Delays, Presented at the 86th Annual Meeting of the Transportation Research Board, January 2007, Washington, DC.

Zhu, F., Ukkusuri, S. V. 2015. A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment. Transportation Research Part C: Emerging Technologies. 55, 363–378. DOI:

Zöldy, M. (2018). Investigation of autonomous vehicles fit into traditional type approval process. Proceedings of ICCTE, 517–521.

Waller, S.T., Ziliaskopoulos, A.K. “A Combinatorial user optimal dynamic traffic assignment algorithm”, Annals of Operations Research, Volume 144, pp. 249–261, 2006. DOI: