Analysis of methods for accounting cargo vehicles in traffic flow of a regulated crossroad

Introduction. The formation of a ‘cargo frame’ around large cities leads to a change in the composition of the traffic flow on bypass roads, and an increase in the total traffic flow of trucks of various categories. In addition, the active development of suburban areas with residential complexes contributes to an increase in traffic. The totality of the reflected phenomena leads to the emergence of a certain kind of transport problems, primarily associated with a decrease in throughput. Quite often, such problems are observed at regulated intersections, which requires a prompt change in the control mode; for this, the necessary measure is the mandatory consideration of the technical and dynamic parameters of trucks, which are not fully taken into account in the existing reduction factors. In order to establish the degree of influence of these parameters on the change in the main characteristics of the traffic flow, such as the average travel time and average speed, this study was carried out.

Methods and materials. When performing the study, the methods of natural observation, statistical analysis and modelling were applied. The necessary materials for the study were devices for automatic collection of traffic flow characteristics, such as video cameras and traffic detectors, Any Logic version 8.0 for modelling, and a package of descriptive statistics in MS Excel.

Results. In the course of the study and the experiment, a difference in the main characteristics of the traffic flow when using standard reduction factors and without using them, taking into account the dynamic and technical parameters of trucks was established. At the object of the study, the difference in the value of the average travel time () for various methods of accounting for trucks, observed in the range [-51.5%; 16.8%] and average speed () in the range [20%; 34%] was determined. As a result of mathematical research, functional relationships between the average speed and traffic intensity are determined, taking into account the presence of trucks of various categories, their technical and dynamic parameters. The ways of further research are determined.

1. Kirpichnikov A. P., Rizaev I. S., Miftahutdinov D. I., Bujnova E. L. Analiz slozhnosti gorodskoj transportnoj seti [Analysis of the complexity of the urban transport network]. Vestnik Tehnologicheskogo universiteta. 2019; T. 22. No 3:123-127. (In Russ.)

2. Baskov V. N., Isaeva E. I., Ignatov A. V. Ocenka ulichno-dorozhnoj seti po pomehonasyshhennosti [Evaluation of the street-road network by noise saturation]. Mir transporta i tehnologicheskih mashin. 2019; 4 (67): 66-72. (In Russ.)

3. Pavlov V. V. Transportno-logisticheskie kompleksy: sovremennoe sostojanie, osobennosti, perspektivy razvitija [Transport and logistics complex es: current state, features, development prospects]. Jekonomika i predprinimatel’stvo. 2016; 11-3 (76): 946-951. (In Russ.)

4. Golovcova I. G., Dovgenko I. A. Metody povyshenija konkurentosposobnosti transportno-logisticheskih kompleksov [Methods for improving the competitiveness of transport and logistics complexes]. Teorija i praktika obshhestvennogo razvitija. 2016; 4: 59-61. (In Russ.)

5. Isakov K., Stasenko L. N., Altybaev A. S., Daiyrbekova D. Influence of parameters of the trafficlight regulation cycle on the road capacity of regulated intersections. The Russian Automobile and Highway Industry Journal. 2019;16 (2): 146-155. (In Russ.) https://doi.org/10.26518/2071-7296-2019-2-146-155

6. Novikov A., NovikovI., Shevtsova A. Modeling of traffic-light signalization depending on the quality of traffic flow in the city. Journal of Applied Engineering Science. 2019; Vol. 17. No 2: 175-181. DOI:10.5937/jaes17-18117.

7. Novikov A., Katunin A., NovikovI., Shevtso va A. Research of Influence of Dynamic Characteristics for Options Controlled Intersection. Procedia Engineering. 2017; 187: 664-671. DOI10.1016/j.proeng.2017.04.429.

8. Vlasov A. A., Pilgeikina I. A., Skorikova I. A. Methods of formation of multiprogram control of an isolated intersection [Metodika formirovanija mnogoprogrammnogo upravlenija izolirovannym perekrestkom]. Komp’juternye issledovanija i modelirovanie. 2021; T. 13. No. 2: 295-303. DOI:10.20537/2076-7633-2021-13-2-295-303. (In Russ.)

9. Shevtsova A. G., Burlutskaya, A. G., Yung, A. A. Ocenka vlijanija parametrov avtomobilej na znachenie potoka nasyshhenija [Estimation of the influence of car parameters on the value of the saturation flow]. Intellekt. Innovacii. Investicii. 2022; 1: 126-134. DOI:10.25198/2077-7175-2022-1-126. (In Russ.)

10. Rassoha V. I., Nikitin N. A., Savina Ju. Je. Sravnenie jeffektivnosti algoritmov raschjota rezhima raboty svetofornogo ob’ekta [Comparison of the efficiency of algorithms for calculating the operating mode of a traffic light object]. Tehniko-tehnologicheskie problemy servisa. 2020; 4 (54): 44-49. (In Russ.)

11. Andronov S. A. Sravnenie jeffektivnosti adaptivnyh algoritmov svetofornogo regulirovanija v srede AnyLogic [Comparison of the efficiency of adaptive traffic light control algorithms in the AnyLogic environment]. Programmnye produkty i sistemy. 2019; 1:150-158. (In Russ.)

12. Skakal’skaja E. D., Samojlova I. A. Razrabotka modeli perekrestka sredstvami AnyLogic [Development of an intersection model using AnyLogic]. Molodoj uchenyj. 2022; 21 (416): 209-211. (In Russ.)

13. KazmiS. M. M., SunXu., Yu H. [et al.]. Solving a Traffic Congestion Problem at T-intersections using AnyLogic Simulation. Conference of Open Innovations Association. FRUCT. 2022; 32: 359-365.

14. Kojnova A. S. Ispol’zovanie AnyLogic dlja modelirovanija transportnyh processov [Using AnyLogic for modeling transport processes]. Nauchnyj al’manah. 2017; 1-3 (27): 83-85. DOI:10.17117/na.2017.01.03.083. (In Russ.)

15. Reenko N. A., Mihajlov A. S. Razrabotka imitacionnoj modeli dorozhnogo dvizhenija v programmnoj srede Anylogic [Development of a traffic simulation model in the Anylogic software environment]. Reshetnevskie chtenija. 2018; T. 2: 153-155. (In Russ.)

16. Dorohin S. V., Lihachev D. V., ArtemovA. Ju., Marusin A. V. Modelirovanie processa dvizhenija na magistral’noj ulice G. Voronezh v programmnoj srede Any Logic [Modeling the process of traffic on the main street of Voronezh in the Any Logic software environment]. Voronezhskij nauchno-tehnicheskij Vestnik. 2022; T. 4. No 4 (42): 73-84. DOI:10.34220/2311-88732022-73-84. (In Russ.)

17. Zyrjanov V. V. Metody ocenki adekvatnosti rezul’tatov modelirovanija [Methods for assessing the adequacy of modeling results]. Inzhenernyj vestnik Dona. 2013; 2 (25): 132. (In Russ.)

18. Novikov A., Glagolev S., NovikovI., Shevtsova A. Information technologies and management of transport systems development of the approach to assessing adaptation of the intersection transport model. IOP Conference Series, ICI2AE 2019, Irkutsk, May 27 01 2019. Vol. 632. Irkutsk: Institute of Physics Publishing, 2019. P. 012052. DOI: 10.1088/1757899X/632/1/012052

19. Novikov A., Novikov I., Katunin A., Shevtsova A. Adaptation Capacity of the Traffic Lights Control System (TSCS) as to Changing Parameters of Traffic Flows Within Intellectual Transport Systems (ITS). Transportation Research Procedia: 12th International Conference “Organization and Traffic Safety Management in Large Cities”, SPbOTSIC 2016, Saint-Petersburg, September 28-30, 2016. Vol. 20. Saint-Petersburg: Elsevier B. V., 2017. P. 455-462. DOI: 10.1016/j.trpro.2017.01.074

20. Novikov I. A., Shevtsova A. G., Kravchen ko A. A., Burlutskaia A. G. Development of a procedure for adapting a model of adjustable intersection. The Russian Automobile and Highway Industry Journal. 2020; 17 (6): 726-735. (In Russ.) https://doi.org/10.26518/2071-7296-2020-17-6-726-735

21. Donchenko V. V., Shumskiy A. N. Estimation of truck reduction factors applicable to calculation of parameters of a regulated intersection. The Russian Automobile and Highway Industry Journal. 2021; 18 (5): 544-553. (In Russ.) https://doi.org/10.26518/20717296-2021-18-5-544-553

22. Novikov I. A., Medvedev M. I., Shevcova A. G. Vlijanie dinamicheskih harakteristik gruzovogo avtotransporta na parametry reguliruemogo perekresta [Influence of the dynamic characteristics of trucks on the parameters of the adjustable cross]. Mir transporta i tehnologicheskih mashin. 2017; 1 (56): 62-69. (in Russ.)

23. Levashev A. G., Mihajlov A. Ju. Utochnenie kojefficientov privedenija k legkovomu avtomobilju dlja raschetov rezhimov regulirovanija [Refinement of the coefficients of reduction to a passenger car for the calculation of control modes]. Vestnik Irkutskogo gosudarstvennogo tehnicheskogo universiteta. 2005; 1 (21): 138-143. (in Russ.)

24. Volkova E. V., Stepanenko A. A. An analysis of traffic flow distribution on roads. IOP Conference Series: Materials Science and Engineering: 3, New Technologies and Targeted Development Priorities, Irkutsk, April 23–24, 2020. Irkutsk, 2020. P. 012074. DOI:10.1088/1757-899X/880/1/012074.

25. Boyko A.F., Kudenikov E.Yu. Tochnyj metod rascheta neobhodimogo kolichestva povtornyh opytov [Accurate method for calculating the required number of repeated experiments]. Vestnik Belgorodskogo gosudarstvennogo tehnologicheskogo universiteta im. V.G. Shuhova. 2016; 8: 128-132. (inRuss.)