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Multi-Vehicle Environment Simulation Tool to Develop and Evaluate Automated Driving Systems in Motorway

고속도로에서의 자율주행 알고리즘 개발 및 평가를 위한 다차량 시뮬레이션 환경 개발

  • Received : 2016.11.10
  • Accepted : 2016.12.27
  • Published : 2016.12.31

Abstract

Since real road experiments have many restrictions, a multi-vehicle traffic simulator can be an effective tool to develop and evaluate fully automated driving systems. This paper presents multi-vehicle environment simulation tool to develop and evaluate motorway automated driving systems. The proposed simulation tool consists of following two main parts: surrounding vehicle model and environment sensor model. The surrounding vehicle model is designed to quickly generate rational complex traffic situations of motorway. The environment sensor model depicts uncertainty of environment sensor. As a result, various traffic situations with uncertainty of environment sensor can be proposed by the multi-vehicle environment simulation tool. An application to automated driving system has been conducted. A lane changing algorithm is evaluated by performance indexes from the multi-vehicle environment simulation tool.

Keywords

References

  1. K. N. Qureshi and A. H. Abdullah, 2013, "A survey on intelligent transportation systems," Middle-East Journal of Scientific Research, vol. 15, pp. 629-642.
  2. AutoNet2030, 2014, Co-operative Systems in Support of Networked Automated Driving by 2030.
  3. R. Bours, M. Tideman, U. Lages, R. Katz, and M. Spencer, 2014, "Automated generation of virtual driving scenarios from test drive data," in Proceedings of FISITA World Congress.
  4. B. Y. Jie, Zhang, Ning, Bian, JianPeng, Shi, Ling, Jin, XiCheng, Wang, JianGuang, Zhou, Zhao Ma, Yong Chen - Dong Feng Motor Corporation, D.-J. U. WeiWen, and H.-T. HanZhi, 2014, "Simulation and Testing of Advanced Driver Assistance System Based on Environmental Model of Pedestrian-Vehicle-Road," in FISITA 2014 World Automotive Congress, Maastricht, Netherlands.
  5. D. Zhao, H. Peng, S. Bao, K. Nobukawa, D. LeBlanc, and C. Pan, 2016, "Accelerated evaluation of automated vehicles using extracted naturalistic driving data," in The Dynamics of Vehicles on Roads and Tracks: Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics (IAVSD 2015), Graz, Austria, 17-21 August 2015, p. 287.
  6. C. Maag, D. Muhlbacher, C. Mark, and H. P. Kruger, 2012, "Studying Effects of Advanced Driver Assistance Systems (ADAS) on Individual and Group Level Using Multi-Driver Simulation," IEEE Intelligent Transportation Systems Magazine, Vol. 4, pp. 45-54. https://doi.org/10.1109/MITS.2012.2203231
  7. M. Tideman, R. Bours, H. Li, T. Schulze, and T. Nakano, 2013, "Integrated simulation toolset for ada system development," in Proceedings of the FISITA 2012 World Automotive Congress, pp. 25-36.
  8. C. Sommer, 2011, "Bidirectionally coupled network and road traffic simulation for improved IVC analysis," IEEE transactions on mobile computing., Vol. 10, p. 3. https://doi.org/10.1109/TMC.2010.133
  9. C. Wissing, T. Nattermann, K.-H. Glander, A. Seewald, and T. Bertram, 2016, "Environment Simulation for the Development, Evaluation and Verification of Underlying Algorithms for Automated Driving," in AmE 2016-Automotive meets Electronics; 7th GMM-Symposium, pp. 1-6.
  10. R. Schubert, Mattern, N., Bours, R., 2014, "Evaluating Automated Vehicle Systems using Probabilistic Sensor Simulations," in ITS European Congress, Helsinki, Finland.
  11. K. Abdelgawad, S. Henning, P. Biemelt, S. Gausemeier, and A. Trachtler, 2016, "Advanced Traffic Simulation Framework for Networked Driving Simulators," IFAC-PapersOnLine, Vol. 49, pp. 101-108.
  12. 문승욱, 2011, "Adaptive cruise control with collision avoidance for multi-vehicle traffics / 문승욱," 다차량 주행상황에서의 전구간 순항주행 및 충돌방지를 위한 차량제어, 서울 : 서울대학교 대학원, 2011, 서울.

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