The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Development of Evaluation Indicators for Optimizing Mixed Traffic Flow Using Complexed Multi-Criteria Decision Approaches

다기준 복합 가중치 결정 기반 혼재 교통류 최적화 평가지표 개발

  • Donghyeok Park (Dept. of Transportation and Logistics Eng., Hanyang University ERICA) ;
  • Nuri Park (Dept. of Smart City Eng., Hanyang University ERICA) ;
  • Donghee Oh (Dept. of Smart City Eng., Hanyang University ERICA) ;
  • Juneyoung Park (Dept. of Transportation and Logistics Eng., Smart City Eng., Hanyang University ERICA)
  • 박동혁 (한양대학교 ERICA 교통물류공학과 ) ;
  • 박누리 (한양대학교 ERICA 스마트시티공학과) ;
  • 오동희 (한양대학교 ERICA 스마트시티공학과) ;
  • 박준영 (한양대학교 ERICA 교통물류공학과.스마트시티공학과)
  • Received : 2024.02.08
  • Accepted : 2024.03.14
  • Published : 2024.04.30
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Abstract

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

자율주행 기술은 상용화될 경우 교통 네트워크에 안전성, 이동성, 환경성을 개선할 잠재력을 지니고 있다. 그러나, 센서 기능의 저하와 원거리 검지의 한계는 자율주행 차량의 안전한 주행을 방해할 수 있으므로 인근 차량과 인프라에서 수집한 정보를 활용하여 보완하는 자율협력주행이 필수적이다. 또한, HDV, AV, CAV는 인지할 수 있는 정보의 범위가 각기 다르고 이에 따른 대응 프로토콜이 상이하기 때문에 자율주행 기술 과도기에 발생하는 혼재 교통류에서의 대응책이 필요하다. 자율주행 차량 보급률, 도로 구간별 특성 차이를 복합적으로 고려한 교통류 최적화 연구가 부족하다. 본 연구는 인프라 가이던스 유스케이스 및 자율주행차량 MPR별 안전성, 이동성, 환경성에 따른 가중치를 개발하는 것을 목적으로 한다. AHP 가중치를 개발하기 위해 MPR을 고려한 Hybrid AHP와 인프라 가이던스 구간 및 상황 별 AHP를 결합하고 통합 평가지표를 개발하였다. 분석결과, LOS A-B × MPR 10% × 분·합류부 및 엇갈림구간은 안전성 가중치(0.841)가 가장 높은 구간인 동시에 이동성 가중치(0.112)가 가장 낮은 구간이였으며, LOS A-B × MPR 50% × CAV 전용도로의 안전성 가중치(0.605)가 가장 낮은 구간인 동시에 이동성 가중치(0.335)가 가장 높은 구간으로 도출되었다. 본 연구의 결과를 기반으로 혼재 교통류를 최적화하기 위한 차량 별 통행 우선권을 부여하는데 활용할 수 있다.

Keywords

Acknowledgement

본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호 RS-2022-00142565)

References

  1. Ahmed, H. U., Huang, Y., Lu, P. and Bridgelall, R.(2022), "Technology developments and impacts of connected and autonomous vehicles: An overview", Smart Cities, vol. 5, no. 1, pp.382-404.
  2. Al-Turki, M., Ratrout, N. T., Rahman, S. M. and Reza, I.(2021), "Impacts of autonomous vehicles on traffic flow characteristics under mixed traffic environment: Future perspectives", Sustainability, vol. 13, no. 19, 11052.
  3. Chen, M., Zhou, L. and Lee, H.(2022), "A study on the safety policies of truck traffic using fuzzy-AHP", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 21, no. 2, pp.44-61.
  4. Cho, S. K. and Lee, J. S.(2006), "Development of the attributes and their weights for evaluation of amenity of Seoul by applying fuzzy-AHP", Seoul Stud, vol. 7, pp.1-16.
  5. Emzivat, Y., Ibanez-Guzman, J., Martinet, P. and Roux, O. H.(2017), "Dynamic driving task fallback for an automated driving system whose ability to monitor the driving environment has been compromised", In 2017 IEEE Intelligent Vehicles Symposium (IV), IEEE, pp.1841-1847.
  6. Faghani, A., Guo, L., Wright, M. E., Hughes, M. C. and Vaezi, M.(2022), "Construction and case study of a novel lung cancer risk index", BMC Cancer, vol. 22, no. 1, 1275.
  7. Fagnant, D. J. and Kockelman, K.(2015), "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations", Transportation Research Part A: Policy and Practice, vol. 77, pp.167-181.
  8. Garg, M., Johnston, C. and Bouroche, M.(2021), "Can Connected Autonomous Vehicles really improve mixed traffic efficiency in realistic scenarios?", In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), IEEE, pp.2011-2018.
  9. Gonzalez-Prida, V., Viveros, P., Barbera, L. and Marquez, A. C.(2014), "Dynamic analytic hierarchy process: AHP method adapted to a changing environment", Journal of Manufacturing Technology Management, vol. 25, no. 4, pp.457-475.
  10. Hobert, L., Festag, A., Llatser, I., Altomare, L., Visintainer, F. and Kovacs, A.(2015), "Enhancements of V2X communication in support of cooperative autonomous driving", IEEE Communications Magazine, vol. 53, no. 12, pp.64-70.
  11. Hong, S. M.(2013), Methodology for Designing Pavement Marking to Reduce Vehicle Speed and Emission on Freeway Off-ramp, Master thesis, Hanyang University.
  12. Jeon, H. M., Yang, I. C., Kim, H. S., Lee, J. H., Kim, S. K. and Jang, J. Y.(2022), "A study on methodology to develop use cases of infra-guidance service for connected and automated driving", Journal of Digital Contents Society, vol. 23, no. 7, pp.1331-1340.
  13. Joo, S. H., Lee, G. W. and Oh, C.(2019), "A multi-criteria analysis framework including environmental and health impacts for evaluating traffic calming measures at the road network level", International Journal of Sustainable Transportation, vol. 13, no. 1, pp.15-23.
  14. Li, T., Guo, F., Krishnan, R., Sivakumar, A. and Polak, J.(2020), "Right-of-way reallocation for mixed flow of autonomous vehicles and human driven vehicles", Transportation Research Part C: Emerging Technologies, vol. 115, 102630.
  15. Li, Z. and Sinha, K. C.(2009), "Methodology for the determination of relative weights of highway asset management system goals and of performance measures", Journal of Infrastructure Systems, vol. 15, no. 2, pp.95-105.
  16. Malikopoulos, A. A., Hong, S., Park, B. B., Lee, J. and Ryu, S.(2018), "Optimal control for speed harmonization of automated vehicles", IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 7, pp.2405-2417.
  17. Miller, G. A.(1956), "The magical number seven, plus or minus two: Some limits on our capacity for processing information", Psychological Review, vol. 63, no. 2, p.81.
  18. Mohan, D., Bangdiwala, S. I. and Villaveces, A.(2017), "Urban street structure and traffic safety", Journal of Safety Research, vol. 62, pp.63-71.
  19. Morando, M. M., Tian, Q., Truong, L. T. and Vu, H. L.(2018), "Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures", Journal of Advanced Transportation, vol. 2018.
  20. Palaniappan, K. and Kum, I. Y. S.(2019), "Underlying causes behind research study participants' careless and biased responses in the field of sciences", Current Psychology, vol. 38, no. 6, pp.1737-1747.
  21. Park, J., Oh, C. and Chang, M.(2013), "A study on variable speed limit strategies in freeway work zone using multi-criteria decision making process", Journal of Korean Society of Transportation, vol. 31, no. 5, pp.3-15.
  22. Park, N., Yang, S. and Park, J.(2023), "Developing a New Hybrid Analytic Hierarchy Process to Evaluate Managed Lanes for Autonomous Vehicles", In 2023 Transportation Research Board 102nd Annual Meeting, Transportation Research Board.
  23. Peng, Y., Song, G., Guo, X. and Guo, M.(2023), "Impact of fundamental elements of connected and autonomous technology on right-turn gap acceptance behavior at an uncontrolled intersection", Journal of Transportation Engineering, Part A: Systems, vol. 149, no. 3, 04022155.
  24. Saaty, T. L.(1977), "A scaling method for priorities in hierarchical structures", Journal of Mathematical Psychology, vol. 15, no. 3, pp.234-281.
  25. SAE(Society of Automotive Engineers International)(2020), Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles J3216_202005, pp.1-20.
  26. SAE(Society of Automotive Engineers International)(2021), Taxonomy and Definitions for Terms Related to Driving Automation for On-Road Motor Vehicles J3016_202104, pp.1-41.
  27. Sun, C., Deng, Z., Chu, W., Li, S. and Cao, D.(2021), "Acclimatizing the operational design domain for autonomous driving systems", IEEE Intelligent Transportation Systems Magazine, vol. 14, no. 2, pp.10-24.
  28. van Beinum, A., Farah, H., Wegman, F. and Hoogendoorn, S.(2018), "Driving behaviour at motorway ramps and weaving segments based on empirical trajectory data", Transportation Research Part C: Emerging Technologies, vol. 92, pp.426-441.
  29. Xu, Z. and Liao, H.(2013), "Intuitionistic fuzzy analytic hierarchy process", IEEE Transactions on Fuzzy Systems, vol. 22, no. 4, pp.749-761.
  30. Ye, L. and Yamamoto, T.(2019), "Evaluating the impact of connected and autonomous vehicles on traffic safety", Physica A: Statistical Mechanics and its Applications, vol. 526, 121009.
  31. Yun, I., Han, E., Lee, C. K., Rho, J. H., Lee, S. and Kim, S. B.(2013), "Mobility and safety evaluation methodology for the locations of Hi-PASS lanes using a microscopic traffic simulation tool", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 12, no. 1, pp.98-108.
  32. Zhang, G., Ye, J., Wang, Y. and Jing, W.(2018), "Comparative Analysis of Different Driving Rules in Freeways Based on Cellular Automata Model and Analytic Hierarchy Process", In CICTP 2017: Transportation Reform and Change-Equity, Inclusiveness, Sharing, and Innovation, VA: American Society of Civil Engineers, pp.3822-3832.