DOI QR코드

DOI QR Code

VENTOS-Based Platoon Driving Simulations Considering Variability

가변성을 고려하는 VENTOS 기반 군집 자율주행 시뮬레이션

  • Received : 2020.10.14
  • Accepted : 2020.10.22
  • Published : 2021.02.28

Abstract

In platoon driving, several autonomous vehicles communicate to exchange information with each other and drive in a single cluster. The platooning technology has various advantages such as increasing road traffic, reducing energy consumption and pollutant emission by driving in short distance between vehicles. However, the short distance makes it more difficult to cope with an emergency accident, and accordingly, it is difficult to ensure the safety of platoon driving, which must be secured. In particular, the unexpected situation, i.e., variability that may appear during driving can adversely affect the safety of platoon driving. Because such variability is difficult to predict and reproduce, preparing safety guards to prevent risks arising from variability is a challenging work. In this paper, we studied a simulation method to avoid the risk due to the variability that may occur while platoon driving. In order to simulate safe platoon driving, we develop diverse scenarios considering the variability, design and apply safety guards to handle the variability, and extends the detail functions of VENTOS, an open source platooning simulator. Based on the simulation results, we have confirmed that the risks caused form the variability can be removed, and safe platoon driving is possible. We believe that our simulation approach will contribute to research and development to ensure safety in platoon driving.

군집주행은 여러 대의 자율 주행 차량이 통신을 사용하여 서로 정보를 교환하며 하나의 군집을 이루어 주행하는 것이다. 이러한 군집주행 기술은 더 좁은 차량 간 간격을 유지하며 주행함으로써 도로의 통행량 증대, 에너지 소비 및 오염물질 배출 감소 등의 다양한 장점을 가진다. 그러나 군집주행의 좁은 차량 간 간격은 긴급한 사고 발생 시 대처를 더 어렵게 만들며, 이에 따라 필수적으로 확보되어야 할 군집주행의 안전성을 보장하는데 어려움을 주고 있다. 특히 주행 중 나타날 수 있는 가변성은 군집주행의 안전에 악영향을 미칠 수 있다. 이러한 가변성은 발생 예측이 어렵고, 재현이 어려운 특성으로 인해 가변성으로부터 발생하는 위험 요소를 방지하는 안전대책 마련에 어려움이 있다. 본 논문에서는 군집주행 중에 생겨날 수 있는 가변성에 따른 위험을 회피하기 위한 시뮬레이션 방법을 연구하였다. 이를 위해 가변성을 고려하는 다양한 시나리오를 개발하고, 가변성을 핸들링할 수 있는 안전 대책을 고안, 적용하였으며, 또한 오픈소스 군집주행 시뮬레이터인 VENTOS를 확장하여 시나리오 시뮬레이션을 수행하였다. 그 결과 가변성으로 인한 군집주행의 위험성을 제거하여 안전한 군집주행이 가능함을 확인하였다. 제시하는 가변성 대응 시나리오 시뮬레이션은 군집주행에서의 안전성을 확보하기 위한 연구 개발에 기여할 것으로 판단한다.

Keywords

References

  1. C. Bergenhem, S. Shladover, E. Coelingh, C. Englund, and S. Tsugawa, "Overview of platooning systems," In Proceedings of the 19th ITS World Congress, Vienna, EU-00336, 2012.
  2. E. Larsson, G. Sennton, and J. Larson, "The vehicle platooning problem: Computational complexity and heuristics," Transportation Research Part C: Emerging Technologies, Vol.60, pp.258-277, 2015. https://doi.org/10.1016/j.trc.2015.08.019
  3. A. Davila, E. del Pozo, E. Aramburu, and A. Freixas, "Environmental benefits of vehicle platooning," SAE Technical Paper, No.2013-26-0142, 2013.
  4. N. Ali and J. Hong, "Variability-Considered Hazards Analysis Technique in Collaboration Environments of Multiple Cyber-Physical Systems," Journal of Korean Institute of Information Scientists and Engineers, Vol.47, No.9, pp.820-834, 2020.
  5. Q. Deng, "A general simulation framework for modeling and analysis of heavy-duty vehicle platooning," IEEE Transactions on Intelligent Transportation Systems, Vol.17, No.11, pp.3252-3262, 2016. https://doi.org/10.1109/TITS.2016.2548502
  6. VENTOS [Internet], https://maniam.github.io/VENTOS/ at Jul. 2020.
  7. M. Amoozadeh, H. Deng, C. N. Chuah, H. M. Zhang, and D. Ghosal, "Platoon management with cooperative adaptive cruise control enabled by VANET," Vehicular Communications, Vol.2, No.2, pp.110-123, 2015. https://doi.org/10.1016/j.vehcom.2015.03.004
  8. M. Amoozadeh, A. Raghuramu, C. N. Chuah, D. Ghosal, H. M. Zhang, J. Rowe, and K. Levitt, "Security vulnerabilities of connected vehicle streams and their impact on cooperative driving," IEEE Communications Magazine, Vol.53, No.6, pp.126-132, 2015. https://doi.org/10.1109/MCOM.2015.7120028
  9. J. Erdmann, "Lane-changing model in SUMO," in Proceedings of the SUMO2014 Modeling Mobility with open Data, Berlin, pp.105-123, 2014.
  10. Y. Jo, S. Lee, and C. Oh, "Impacts of Truck Platooning in Mixed-traffic Conditions on Freeway Capacity," Journal of Korean Society of Transportation, Vol.36, No.5, pp.331-345, 2018. https://doi.org/10.7470/jkst.2018.36.5.331
  11. L. Alekszejenko and T. P. Dobrowiecki, "SUMO Based Platform for Cooperative Intelligent Automotive Agents," in Proceedings of the SUMO User Conference 2019, Berlin, pp.107-123, 2019.
  12. J. Mena-Oreja, and J. Gozalvez. "Permit-a SUMO simulator for platooning maneuvers in mixed traffic scenarios," in Proceedings of the 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, 2018, pp.3445-3450.
  13. Z. Yang, X. Wang, X. Pei, S. Feng, D. Wang, J. Wang, and S. C. Wong, "Longitudinal safety analysis for heterogeneous platoon of automated and human vehicles," in Proceedings of the 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, pp.3300-3305, 2018.
  14. N. Ali, H. Manzoor, and J. Hong, "Analyzing Safety of Collaborative Cyber-Physical Systems Considering Variability," IEEE Access, Vol.8, pp.162701-162713, 2020. https://doi.org/10.1109/access.2020.3021460
  15. M. Aki, R. Zheng, K. Nakano, S. Yamabe, S. Y. Lee, Y. Suda, Y. Suzuki, and H. Ishizaka, "Evaluation of safety of automatic platoon-driving with improved brake system," in Proceedings of the 19th ITS World CongressERTICO-ITS EuropeEuropean CommissionITS AmericaITS Asia-Pacific, Vienna, AP-00336, 2012.
  16. S. Y. Lee and C. Oh, "Lane Change Behavior of Manual Vehicles in Automated Vehicle Platooning Environments," Journal of Korean Society of Transportation, Vol.35, No.4, pp.332-347, 2017. https://doi.org/10.7470/jkst.2017.35.4.332
  17. Y. Song, and H. K. Choi, "WAVE System Performance for Platooning Vehicle Service Requirements Under Highway Environments," The Journal of The Korea Institute of Intelligent Transport Systems, Vol.16, No.1, pp.147-156, 2017. https://doi.org/10.12815/kits.2017.16.1.147
  18. E. Chan, "Overview of the sartre platooning project: technology leadership brief," SAE Technical Paper, No. 2012-01-9019, 2012.
  19. S. Ellwanger and E. Wohlfarth, "Truck platooning application," In Proceedings of the 2017 IEEE Intelligent Vehicles Symposium (IV), Redondo Beach, pp.966-971, 2017.
  20. L. Aarts and G. Feddes, "European truck platooning challenge," In Proceedings of the In HVTT14: International Symposium on Heavy Vehicle Transport Technology, Rotorua, 2016.
  21. Nikkei Asia, Japan launches test of self-driving truck convoys [Internet], https://asia.nikkei.com/Editor-s-Picks/Japan-Update/Japan-launches-test-of-self-driving-truck-convoys at June 2020.
  22. K. Serizawa, M. Mikami, K. Moto, and H. Yoshino, "Field trial activities on 5G NR V2V direct communication towards application to truck platooning," In Proceedings of the 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, pp.1-5, 2019.
  23. G. Jun, S. Kim, S. Lee, C. Kim, J. Park, "A Study on the Operational Results of SMART Highway Test-bed," The Journal of the Korea Institute of Intelligent Transport Systems, Vol.14, No.4, pp.27-39, 2015. https://doi.org/10.12815/kits.2015.14.4.027
  24. H. Hartenstein and K. Laberteaux, "VANET: Vehicular applications and inter-networking technologies (Vol.1)," John Wiley & Sons, 2009.
  25. L. Xiao, M. Wang, and B. van Arem, "Realistic CarFollowing Models for Microscopic Simulation of Adaptive and Cooperative Adaptive Cruise Control Vehicles," Transportation Research Record: Journal of the Trans. Research Board, Vol.2623, No.1, pp.1-9, 2017. https://doi.org/10.3141/2623-01
  26. L. Xiao, M. Wang, W. Schakel, and B. van Arem, "Unravelling effects of cooperative adaptive cruise control deactivation on traffic flow characteristics at merging bottlenecks," Transportation Research Part C: Emerging Technologies, Vol.96, pp.380-397, 2018. https://doi.org/10.1016/j.trc.2018.10.008
  27. S. Cheon, "An Overview of Automated Highway Systems (AHS) and the Social and Institutional Challenges They Face," UC Berkeley: University of California Transportation Center, 2003.
  28. SUMO [Internet], https://www.eclipse.org/sumo/at Jun. 2020.
  29. OMNET++ [Internet], https://omnetpp.org/ at Jun. 2020.
  30. P. G. Gipps, "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Vol.15, No.2, pp.105-111, 1981. https://doi.org/10.1016/0191-2615(81)90037-0