All Issue

2023 Vol.41, Issue 4 Preview Page

Article

Traffic Signal Plan Update Algorithm Analysis

교통 신호 계획 업데이트 알고리즘 연구

Yeonsoo KIM1
,
Yohee HAN2*
,
Youngchan KIM3
김 연수1
,
한 여희2*
,
김 영찬3
1Master’s Degree, Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea
2Research Professor, Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea
3Professor, Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea
1서울시립대학교 교통공학과 석사과정
2서울시립대학교 교통공학과 연구교수
3서울시립대학교 교통공학과 교수
*Corresponding Author
31 August 2023. pp. 483-494
PDF XML Citation
Abstract

In this study, we propose an algorithm for periodically updating the signal plans of individual intersections based on traffic data. The algorithm is based on a detection system that can collect traffic volume by movement type and initial queue lengths through video detection devices. It establishes an algorithm that determines whether to optimize the signals of a specific intersection based on the time of day, and optimizes the signals of intersections deemed to require optimization. The proposed algorithm can calculate the optimal signal plan based on the Webster model, minimizing delays at intersections and for different movements while equalizing the delay levels of movements within the intersection. Unlike signal plans that are updated on an annual basis, the algorithm produces signal plans at shorter intervals, enabling efficient operations that reflect relatively recent traffic conditions. To evaluate the effectiveness of the developed signal plan update algorithm, simulation analysis was conducted by simulating real-world scenarios in VISSIM. The simulation analysis confirmed that the signal plans generated by the signal plan update algorithm improve the service level of individual intersections and reduce variations in service levels among different movement types within the intersection. The traffic signal plan update algorithm is significant in that it enables suitable signal operations based on the latest traffic conditions by periodically reflecting the traffic situation, especially at intersections where real-time signal control is challenging.

Keywords
periodically updating algorithm
traffic signal optimization
transportation historical data
video detection system
webster model

본 연구에서는 교통 자료를 기반으로 개별 교차로의 신호 계획을 주기적으로 업데이트하는 알고리즘을 제안하였다. 영상검지기를 통해 이동류별 교통량 및 초기 대기 차량 대수 정보를 수집할 수 있는 검지 체계를 기반으로 교통 이력 자료를 수집하여, 기존에 정해진 요일별 시간대별 교차로의 신호 운영 계획을 최적화할지 판단하여 최적화가 필요하다고 판단된 시간대의 신호를 최적화하는 과정이 담긴 알고리즘을 정립하였다. 연구에서 논하는 알고리즘은 Webster 모형 기반의 최적 신호를 계산하여 교차로의 지체와 이동류의 지체를 최소화하고 교차로 내 이동류의 지체 수준을 균등화하는 신호 계획을 산출한다. 교통 신호 계획 업데이트 알고리즘은 비교적 짧은 주기로 최신 교통상황에 적합한 신호 계획을 산출하고 운영자에게 최적 신호 계획을 제공한다. 제안하는 교통 신호 계획 업데이트 알고리즘의 효과평가를 위해 VISSIM 프로그램을 통해 서울시 강남구의 신호 교차로 네트워크를 모사하고 2개 주요 교차로에 대하여 분석을 수행하였다. 시뮬레이션 분석 결과 신호 최적화가 필요한 교차로의 최적 신호를 산출하여 기존 신호 운영 대비 교차로의 종합 서비스수준이 1, 2단계 개선되었으며 교차로 내 이동류별 서비스수준의 편차를 줄여주는 것을 확인하였다. 교통 신호 계획 업데이트 알고리즘은 실시간 신호 제어가 어려운 교차로에서 주기적으로 최근의 교통상황에 적합한 신호 운영을 가능하게 하는 알고리즘이라는 점에서 의의가 있다.

키워드
주기적인 업데이트 알고리즘
교통 신호 최적화
교통 이력 자료
영상검지기
웹스터 모형
References
1
Ahn H. J. (2022), A Study on Traffic Processing Based on Image Detection for Signal Control, University of Seoul, 1-42.
2
An G. H., Go G.Y., Jeong Y. J., Park S. Y. (2016), Smart Signal Management System Development, Korea Society of Road Engineers, 18(3), 35-39.
3
Chen C., Wei H., Xu N., Zheng G., Yang M., Xiong Y., Li Z. (2020), Toward a Thousand lights: Decentralized Deep Reinforcement Learning for Large-scale Traffic Signal Control, In Proceedings of the AAAI Conference on Artificial Intelligence, 34(4), 3414-3421. 10.1609/aaai.v34i04.5744
4
Jeong Y. J. (2018), Determination Method of Signal Timing Plan Using Travel Time Data, Journal of Korean Contents, 18(3), 52-61.
5
Jung Y. J., Kim Y. C., Beak H. S. (2005), Development of The Signal Control Algorithm Using Travel Time Informations of Sectional Detection Systems, J. Korean Soc. Transp., 23(8), Korean Society of Transportation, 181-191.
6
Kim M. J., Han Y. H., Kim Y. C., Lee M. H. (2022), Advanced Real-time Signal Control Based on Image Detection for Equalizing Degree of Saturation, J. Korean Soc. Transp., 40(3), Korean Society of Transportation, 400-410. 10.7470/jkst.2022.40.3.400
7
Kim Y. C., Yoo C. S. (2000), Development of Optimization Model for Traffic Signal Timing in Grid Networks, J. Korean Soc. Transp., 18(1), Korean Society of Transportation, 87-97.
8
Koonce P., Rodegerdts L. (2008), Traffic Signal Timing Manual (No.FHWA-HOP-08-024), United States, Federal Highway Administration.
9
Korean National Police Agency (2019), Smart Signal Management System Development, Seoul, South Korea.
10
Lee G. H., Shin S. I. (2002), Development of A System Optimum Traffic Control Strategy with Cell Transmission Model, J. Korean Soc. Transp., 20(5), Korean Society of Transportation, 193-206.
11
Lee S. H., Son J. C., Jeong S., Hong S. P. (2013), Korea Highway Capacity Manual, Ministry of Land, Transport and Maritime Affairs, 210-325.
12
Seoul Metropolitan Police Agency (2001), Real-time Signal Management System, Seoul, South Korea.
13
Wang Y., Xu T., Niu X., Tan C., Chen E., Xiong H. (2020), STMARL: A Spatio-temporal Multi-agent Reinforcement Learning Approach for Cooperative Traffic Light Control, IEEE Transactions on Mobile Computing, 21(6), 2228-2242. 10.1109/TMC.2020.3033782
14
Wang Y., Yang X., Liang H., Liu Y. (2018), A Review of the Self-adaptive Traffic Signal Control System Based on Future Traffic Environment, Journal of Advanced Transportation. 10.1155/2018/1096123
15
Zheng G., Xiong Y., Zang X., Feng J., Wei H., Zhang H., Li Y., Xu K., Li Z. (2019a), Learning Phase Competition for Traffic Signal Control, In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 1963-1972. 10.1145/3357384.3357900PMC6838901
16
Zheng G., Zang X., Xu N., Wei H., Yu Z., Gayah V., Xu K., Li Z. (2019b), Diagnosing Reinforcement Learning for Traffic Signal Control, arXiv preprint arXiv:1905.04716.
Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 41
  • No :4
  • Pages :483-494
  • Received Date : 2023-04-06
  • Revised Date : 2023-05-04
  • Accepted Date : 2023-07-14
  • DOI :https://doi.org/10.7470/jkst.2023.41.4.483
Journal Informaiton Journal of Korean Society of Transportation Journal of Korean Society of Transportation
Archives
: 2015 Vol.34~
  • scopus
  • NRF
  • KOFST
  • crossref cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close