Available online at ScienceDirect. Transportation Research Procedia 20 (2017 )

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1 Available online at ScienceDirect Transportation Research Procedia 20 (2017 ) th International Conference "Organization and Traffic Safety Management in Large Cities", SPbOTSIC-2016, September 2016, St. Petersburg, Russia Model of Road Traffic Management in the City during Major Sporting Events Ramil Zagidullin* Kazan State University of Architecture and Engineering, 1 Zelenaya Street, Kazan, , Russia Abstract The article deals with issues of road traffic management during major sports events using a simulation package. This research is intended to study the alternatives and models of traffic management during a major sports event in a city. In doing so four alternatives have been selected for an intersection of the streets, for a main three-lane street depending on the intensity of: background traffic flow (NF), public transport (NM) and transport which services the major sports event (NS). Special attention is paid to the movement of traffic flows of different types in a controlled intersection of the street and road network. Based on the analysis of dynamic models of traffic as well as the impact of background traffic flow and public transport on the transport which services a major sports event, we defined the efficiency criteria and specified characteristics of traffic in a street and road network with the right most lane dedicated to public transport The Authors. Published by Elsevier by Elsevier B.V. This B.V. is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the organizing committee of the 12th International Conference "Organization and Traffic Peer-review Safety Management under responsibility in Large of Cities". the organizing committee of the 12th International Conference Organization and Traffic Safety Management in large cities Keywords: Traffic management, traffic modeling, major sports event. * Corresponding author. Tel.: ; fax: address: r.r.zagidullin@mail.ru * The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the organizing committee of the 12th International Conference Organization and Traffic Safety Management in large cities doi: /j.trpro

2 710 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) Introduction Major sports events vary in both the number of participants, venue, duration, scope of sports as well as in transport infrastructure and external factors which affect its functioning [Zagidullin (2012)]. The number of sportsmen and team members who participate in an event can exceed 10,000 people while the number of sold tickets can amount to more than 5 mln. The event can be held on the territory of one city and in several countries (football world championships). Sports events can be grouped in several clusters which are separated by great distances and differ in conditions of transport servicing (plain and mountain areas which are characteristic of winter Olympic Games and Student Games). The number of sports can exceed 30, and more than 300 awards can be granted. Finally, the duration of major sports events can be as long as six weeks. All these factors affect transport servicing of major sports events and give rise to problems which have to be dealt with. These problems originate from the mismatch of an existing transport system capacity of a sport venue with the travel demand and quality requirements for its satisfaction at the time of a sports event. This mismatch is virtually unavoidable during mass sports events normally held in big cities. Today high levels of service of transport systems are typical for all large cities [Zyryanov (2011), Bovy and Liaudat (2003), Carrara (2008), Inaudi and Balister (2003), Zyryanov et al. (2009)]. So giving the priority on the road to client groups, primarily to sportsmen and referees, during a major sports event, is a prerequisite for making the venues of sports events and cultural programs available. However, a dense residential development and historically determined framework of the city street and road network might prevent from reconstructing a road and managing the traffic for a major sports event by means of a dedicated lane [Zagidullin (2015)]. This research is intended to study traffic management alternatives and models during a major sports event in a city. In doing so four alternatives have been selected for an intersection of the streets, for a main three-lane street depending on the intensity of the background road traffic (N F), public transport (N M) and transport for major sporting events (N S): a) without dedicated lanes; b) with a dedicated right most lane for public transport and for transport involved for major sporting events, c) with a dedicated right most lane for public transport; d) with a dedicated right most lane for public transport and left most lane for transport involved for major sporting events [Musin and Zagidullin (2016)]. The scope of research is the process of transport flows in a section of the street and road network which is formed by an intersection of the main six-lane arterial road of a city status and a subsidiary four-lane road of a regional status. The length of each road is 500 m.; the intersection of the roads is located in the geometrical center of the length of both roads. The main road is equipped with public transport stops after the intersection downstream of traffic flow (Fig. 1).

3 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) Fig. 1. Study area of the street and road network. The subject of research is a simulation dynamic model of traffic when vehicles cross a controlled intersection. The model is a partial representation of a simulated reality as far as it is considered satisfactory in terms of the problem being solved. The following conditions are mandatory and sufficient features of a model: a model reflects the original and the form of this similarity is clearly expressed and accurately recorded (reflection condition); a model represents the object of research (representation condition); study of a model provides information (details) about the original (extrapolation condition) [Gorev et al. (2015)]. Simulation is resorted to when the objects of research cannot be analyzed using direct or formal analytical methods [Drew (1972)]. The researchers are based on empirical methods using a simulation package Aimsun with further regression analysis. During the studies we developed an experiment with intentionally changing the levels of variation of factors depending on the experimental conditions, for alternative No.3. Table 1 shows levels and intervals of variation of factors.

4 712 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) Table 1. Levels and intervals of variation of factors. Factors Description of levels Symbols F S M Lower Central Upper Interval of variation ΔХ The factors under investigation were represented as symbols and were calculated by the following formulas: F 2600 S 500 X 1, X , X 3 M, 80 where F flow intensity of background road traffic; S flow intensity of transport for major sporting events; M intensity of public transport. The influence of intensity of background road traffic and the number of vehicles, on the total travel time (traffic speed) was evaluated after the experimental results were processed according to the selected matrix of a three-factor experiment, 27 experiments in total [Musin and Zagidullin (2016)]. Table 2 gives the results of experiments according to five additional evaluation criteria for traffic management in a controlled intersection: delay; stopping time; total time; density; speed. Table 2. Results of simulation experiments for alternative No.3. No. Delay, sec/km Stopping time, sec/km Total time, h Density, vehicle/km Speed, km/h

5 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) The results of statistical analysis of alternative No.3 are represented in Table 3 and Figure 2 shows a graphic representation of traffic rate vs. intensity: a) background traffic flow and transport for major sporting event; b) background traffic flow and public transport; c) transport for major sporting event and public transport. Table 3. Results of statistical analysis. Correlation factor R Multiple R Corrected R F(3.23) p Standard remainder error Number of observations 27 The results of regression of a dependent variable in alternative No.3 are given in Table 4. Table 4. Results of regression of a dependent variable. β Standard error β B Standard error B t(23) p-level Section X X X

6 714 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) a) b)

7 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) c) Fig. 2. Traffic rate vs. intensity: a) background traffic flow and transport for major sporting event; b) background traffic flow and public transport; c) transport for major sporting event and public transport. The regression equation for alternative No.3 is as follows: Т 3 = X X X 3 (1) 2. Conclusion The mathematical model (1) leads to a conclusion that an increase in travel time (traffic rate) of a transport flow in general can be explained by the growth of intensity of the background road traffic in a greater degree (0.631), than by the intensity of public transport (0.4) and transport for major sporting event in a less degree (0.568) under given conditions. Further study of the remaining alternatives of traffic management during a major sporting event using this mathematical model will help to make a comparative analysis of the given alternatives and choose the most effective ones from them. References Bovy, P., Liaudat, C. (2003). Large Event Logistical and Support Traffic Management. Abstract and Summary Report. Lausanne: Swiss Federal Institute of Technology at Lausanne. Carrara, M. (2006). Winter Olympic Games Turin Experience. In proceedings of 15th ITS World Congress, New York. Drew D. (1972). Traffic Flow Theory and Control. Moscow: Transport, 424 p. Gorev, A.E., Bettger, K., Prokhorov, A.V, Gizatullin, R.R. (2015). Fundamentals of Transport Simulation: Practical Guide. Saint Petersburg: LLC Publishing and printing company KOSTA, 168 p. Inaudi, D., Balister, P. (2003). Transport Planning for Torino 2006 Winter Olympic Games. In proceedings of 10th World Congress Intelligent Transport Systems and Services, Madrid. Musin, V.I., Zagidullin, R.R. (2016). Research of Traffic Conditions for Transport for Major Sporting Event with a Dedicated Lane for Public Transport. In proceedings of IV International Research and Practice Conference Modern Life Safety Problems: Intelligent Transport Systems, Kazan: pp

8 716 Ramil Zagidullin / Transportation Research Procedia 20 ( 2017 ) Zagidullin, R.R. (2012). Territorial and Transport Planning of a Major Sporting Event. Bulletin of KSUACE, (3): Zagidullin, R.R. (2015). Specific Features of Traffic Flows in a City during Major Sporting Events. Science and Engineering in Road Industry, (4): 4 6. Zyryanov, V., Keridi, P., Guseynov R. (2009), Traffic Modelling of Network Level System for Large Event. In proceedings of 16th ITS World Congress, Stockholm: 180 p. Zyryanov, V.V. (2011). Simulation during Transport Servicing of Mega Events. Bulletin of Don Engineering, 18(4):