Simulation modeling in GPSS for optimizing the traffic lights cycle of adjustable crossroads

Abstract

The problem of traffic management, especially in big cities is particularly actual. Due to unavoidable motorization increase in number of vehicles has resulted in congestion, traffic jams, difficulty of the movement of pedestrians, increasing the number of accidents. Traffic jams are undesirable because of higher fuel consumption, increased pollution due to exhaust gases as well as noise, etc. The only way to avoid harmful consequences is to optimize the operation of the traffic lights cycle. The purpose of the work is creation the simulation model in GPSS for determining the optimal traffic lights cycle at adjustable crossroads when managing vehicle flows with specified intensities. The mathematical model of adjustable crossroads can be presented as a queuing system. Development of the simulation model includes several stages: programming in GPSS, verification and assessment of the adequacy. The algorithm for optimizing the traffic lights cycle and diagrams are used to find the optimal value of the cycle. The minimum intersection travel time (including time of queuing) is selected as the optimal criterion. The object of study is the traffic lights cycle regulation of the intersection Sovietskaya St. – Rogachevskaya St. – Telman St. in Gomel, Belarus. The existing traffic lights cycle regulation at the intersection Sovietskaya str. – Rogachevskaya str. – Telman str. has been studied. Simulation modeling of the intersection has been created in GPSS and traffic light cycle optimization algorithm has been developed. According to a worked out algorithm the traffic lights cycle at research intersection during saturation flux has been improved. Transport delays both at the existing and optimized crossings have been estimated. Optimization of the traffic lights cycle will increase the traffic capacity of the intersection, reduce the volume of toxic emissions and decrease the accident risk. The developed simulation model can be modified for other types of intersections and used as the basis for a decision support system based on low-level simulation.

Bibliography

1. Anfilets, S. V., & Shut, V. N. (2009). The creation of models of adjustable crossroads on GPSS. Proc. 9th Int. Conf. “Reliability and Statistics in Transportation and Communication”. Riga: Transport and Telecommunication Institute, 433-438.

2. AnyLogic. Mnogopodkhodnoye imitatsionnoye modelirovaniye [AnyLogic. Multi-Approach Simulation]. Retrieved January 30, 2020 from http://www.anylogic.ru.

3. Bandman, O. (2005). Computation properties of spatial dynamics simulation by probabilistic cellular automata. Future Generation Computer Systems, 21, 633-664.

4. Barotova, A.Zh. (2018). Imitatsionnaya model perekrostka s vozmozhnostyu optimizatsii svetofornogo regulirovaniya [Simulation model of the intersection with the ability to optimize traffic light regulation]. Samara: SamGTU [in Russian].

5. Benenson, I., Omer, I., & Hatna, E. (2002). Entity-based modeling of urban residential dynamics: the case of Yaffo, Tel-Aviv. Environment and Planning B: Planning and Design, 29, 491-512.

6. Burdin, I.O., & Minzurenko, A.A. (2016). Imitatsionnoye kompyuternoye modelirovaniye kriticheskikh perekrestkov na primere razvyazki ulitsy Tsimlyanskoy i Vostochnogo obkhoda v gorode Permi [Computer simulation of critical crossroads on the example transp

7. Chen, P., Zeng, W., & Guizhen, Yu. (2019). Assessing right-turning vehicle-pedestrian conflicts at intersections using an integrated microscopic simulation model. Accident Analysis & Prevention, 129, 211–224. https://doi.org/10.1016/j.aap.2019.05.018

8. Ferrer, J., López-Ibanez, M., & Alba, E. (2019). Reliable simulation-optimization of traffic lights in a real-world city. Applied Soft Computing, 78, 697-711. https://doi.org/10.1016/j.asoc.2019.03.016

9. Glimshina, K. A., Bogdanova, D. R., & Yakovleva, D. E. (2017). Imitatsionnoye modelirovaniye perekrestka ulits imeni Goroda Galle i Rikharda Zorge goroda Ufy [Simulation crossroads mr. Halle and Richard Zorge in the city of Ufa]. Materialy 6 Mezhdunarodno

10. Gubanov, N. G., Kozlov, V. V., & Barotova, A. G. (2017). Imitatsionnaya model perekrestka s vozmozhnostyu regulirovaniya dvizheniya [Simulation model of the intersection with the possibility of traffic control] Traditsii i innovatsii v stroitelstve i arkh

11. Ismagilov, T. R., Boyarshinova, I. N., & Potapova, I. A. (2016). Razrabotka kompyuternoy imitatsionnoy modeli avtomobilnogo dvizheniya cherez seriyu perekrostkov [Developing a computer imitational model of vehicular traffic through a series of intersectio

12. Mochalin, A. A., Zaripova, A. A., Shevchenko, A. A., & Abdullin, A. R. (2017). Metod optimizatsii dlitelnosti faz svetofora na perekrestke v programme AnyLogic [The method of optimizing the duration of the phases of a traffic light at the intersection in

13. Rasskazova, M. N., Danilova, A. S., & Sukhovoy, D. V. (2017). Razrabotka imitatsionnoy modeli uchastka dorozhnoy seti g. Simferopolya [Development of a simulation model of the road network of the city of Simferopol] Materialy II Regionalnoy nauchno-tekhni

14. Shevchenko, D. N., & Kravchenya, I. N. (2009). Imitatsionnoye modelirovaniye na GPSS [GPSS simulation: a learning method]. Gomel: BelSUT [in Russian].

15. Taha, Hamdy A. (2007). Operations research: An introduction. 8th ed. New Jersey: Upper Saddle River.