Comprehensive Optimization Strategy of Traffic Signal Control System

Authors

  • Min Wei

DOI:

https://doi.org/10.61173/qdr5j215

Keywords:

Traffic signal control, adaptive control, historical data analysis, discrete control

Abstract

Traffic jams have become a worldwide presence where urban centers are concerned, and it is clearly seen that traditional fixed-time control systems are not as flexible. The systems fail to have some ability to react to real-time traffic conditions, situations that bring a lot of inefficiencies, more fuel consumption, and more emissions. This paper forwards a new data-driven traffic signal control optimization technique, which deploys historical data analysis and real-time adaptive control. Supplying historical traffic pattern data, the presented system estimates traffic volume and makes use of intelligent signal control plans that advocate for movable vehicles and clean lungs. Dynamic control allows the system to adapt by managing the signal via real-time live traffic conditions.

References

[1] Economic Commission for Latin America and the Caribbean (ECLAC), „Traffic congestion: the problem and how to deal with it,“ Santiago, 2020. [Online]. Available: https://repositorio. cepal.org/handle/11362/45560

[2] H. Faheem, A. Shorbagy, and M. Gabr, „Impact of Traffic Congestion on Transportation System: Challenges and Remediations – A review,“ Mansoura Engineering Journal, vol. 49, Jan. 2024, doi: 10.58491/2735-4202.3191.

[3] Y. Zhang, K. Shang, Z. Cui, Z. Zhang, and F. Zhang, „Research on Traffic Flow Prediction at Intersections Based on DT-TCN-Attention,“ Sensors (Basel), vol. 23, no. 15, pp. 6683, Jul. 2023, doi: 10.3390/s23156683.

[4] A. Ikpe and J. Ohwoekevwo, Intelligent Transportation Systems as a Pivotal Instrument in the Development of Smart Cities in the 21st Century. 2024.

[5] A. Naz and I. Hoque, Integration of Intelligent Transportation Systems (ITS) with Conventional Traffic Management in Developing Countries. 2023. doi: 10.31224/3154.

[6] H. R. Ismael, S. Y. Ameen, S. F. Kak, H. M. Yasin, I. M. Ibrahim, A. M. Ahmed, and D. M. Ahmed, „Reliable communications for vehicular networks,“ Asian Journal of Research in Computer Science, vol. 10, no. 2, pp. 33–49, 2021.

[7] C. Kaptan, „Data Analytics-backed Vehicular Crowd-sensing for GPS-less Tracking in Public Transportation“, Doctoral dissertation, Univ. of Ottawa, Ottawa, Canada, 2018.

[8] M. M. Dhaliwal, “An Examination of Downtown Vancouver Streets: Does Pedestrian-oriented Design Actually Foster Increased Pedestrian Usage?” Doctoral dissertation, Simon Fraser University, Vancouver, 2007.

[9] Federal Highway Administration, „Signalized Intersections: An Informational Guide,“ Publication No. FHWA-SA-13-027, U.S. Department of Transportation, Washington, DC, USA, 2013. [Online]. Available: https://safety.fhwa.dot.gov/ Dean&Francis ISSN 2959-6157 intersection/signal/fhwasa13027.pdf

[10] L. Studer, M. Ketabdari, and G. Marchionni, „Analysis of Adaptive Traffic Control Systems Design of a Decision Support System for Better Choices,“ *J. Civil Environ. Eng.*, vol. 5, Jan. 2015, doi: 10.4172/2165-784X.1000195.

[11] S. Moadi, S. Stein, J. Hong, and R. Murray-Smith, “Real- Time Adaptive Traffic Signal Control in a Connected and Automated Vehicle Environment: Optimisation of Signal Planning with Reinforcement Learning under Vehicle Speed Guidance,” Sensors, vol. 22, Oct. 2022, p. 7501, doi: 10.3390/ s22197501.

[12] J. D. Trivedi, M. S. Devi, and D. H. Dave, “A Vision- Based Real-Time Adaptive Traffic Light Control System Using Vehicular Density Value and Statistical Block Matching Approach,” Transport and Telecommunication, vol. 22, no. 1, pp. 87–97, 2021, doi: 10.2478/ttj-2021-0007.

[13] J. Kustija and A. Nur, “SCATS (Sydney Coordinated Adaptive Traffic System) as a Solution to Overcome Traffic Congestion in Big Cities,” *Int. J. Res. Appl. Technol.*, vol. 3, pp. 1-14, May 2023, doi: 10.34010/injuratech.v3i1.7875.

[14] M. Massar, I. Reza, S. M. Rahman, S. M. H. Abdullah, A. Jamal, and F. S. Al-Ismail, “Impacts of Autonomous Vehicles on Greenhouse Gas Emissions-Positive or Negative?” *Int. J. Environ. Res. Public Health*, vol. 18, no. 11, p. 5567, May 2021, doi: 10.3390/ijerph18115567.

[15] T. Dinh, “Managing Traffic Congestion in a City: A Study of Singapore‘s Experiences”. 2019.

[16] Fedorov, A., Nikolskaia, K., Ivanov, S. et al. Traffic flow estimation with data from a video surveillance camera. J Big Data 6, 73 (2019). https://doi.org/10.1186/s40537-019-0234-z

[17] Beijing Municipal Commission of Transport, „Traffic Statistics,“ Beijing Municipal Commission of Transport, 2024. [Online]. Available: https://jtw.beijing.gov.cn/xxgk/jttj/

[18] K. Ogata, Modern Control Engineering, 5th ed. Upper Saddle River, NJ, USA: Prentice Hall, 2010.

[19] S. Baldi, I. Michailidis, V. Ntampasi, E. Kosmatopoulos, I. Papamichail, and M. Papageorgiou, “A simulation-based traffic signal control for congested urban traffic networks,” *Transportation Science*, vol. 53, pp. 1-14, Nov. 2017, doi: 10.1287/trsc.2017.0754.

[20] R. Lichtman, „Managing a low urban emissions world,“ npj Climate Action, vol. 3, no. 1, pp. 44, 2024.

[21] R. Bose, S. Sengupta, and S. Roy, Interpreting SLA and Related Nomenclature in Terms of Cloud Computing: A Layered Approach to Understanding Service Level Agreements in the Context of Cloud Computing. Lambert Academic Publishing, 2023.

[22] L. Mitropoulos, K. Kouretas, K. L. Kepaptsoglou, and E. I. Vlahogianni, „Total Cost of Ownership for Automated and Electric Drive Vehicles,“ in Proc. VEHITS, 2021, pp. 34-43.

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Published

2024-12-31