Driving Environment Reconstruction and Analysis System on Multi-sensor Network

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• 作者：Chunyu Zhang (25)
  Yong Su (25)
  Jiyang Chen (26)
  Wen Wang (25) (27)
  
• 关键词：driving environment reconstruction ; multi ; sensors
• 刊名：Lecture Notes in Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：7419
• 期：1
• 页码：181-191
• 全文大小：351KB
• 参考文献：1. Parker, M.J., Zegeer, C.V.: Traffic conflict techniques for safety and operations. 2008 Observers Manual. Publication. No. FHWA-IP-88-027. U.S. Department of Transportation (January 1989)
  2. Lin, Q., Cheng, B., Lai, J., et al.: A new method for analysis of traffic conflict by using video drive recorders. In: Proceedings of ITS Conference, Beijing (2007)
  3. So, K., Noboru, K., Toshihiro, A., et al.: Analysis o f mechanism of rear end collision accident by drive data recorders. In: Proceedings JSAE Annual Congress; Klauer, S.G., Dingus, T.A., Neale, V.L., et al.: Impact on Driver Inattention on Near Crash/Crash Risk: An Analysis Using the 100 Car Naturalistic, Driving Study Data (Report No. DOT HS 810 594). National Highway Traffic Safety Administration, Washington, DC (2006)
  4. Klauer, S.G., Dingus, T.A., Neale, V.L., et al.: Impact on Driver Inattention on Near Crash/Crash Risk: An Analysis Using the 100 Car Naturalistic Driving Study Data (Report No. DOT HS 810 594). National Highway Traffic Safety Administration, Washington, DC (2006)
  5. Noboru, K., So, K., Tsuyoshi, K., et al.: Analysis o f rear end collision near miss and its occurrence by drive data recorder. In: Proceedings JSAE Annual Congress (2006)
  6. Tetsuya, N., Kenichi, Y., Horishi, N., et al.: Development and validation of a drive recorder for automobile accidents. In: Proceedings JSAE Annual Congress (2000)
  7. Hanowski, R.J., Blanco, M., Nakata, A., Hickman, J.S., Schaudt, W.A., Fumero, M.C., Olson, R.L., Jermeland, J., Greening, M., Holbrook, G.T., Knipling, R.R., Madison, P.: The drowsy driver warning聽system聽field聽operational聽test,聽data聽collection聽methods聽final聽report.聽Report聽No.聽DOT聽HS聽810聽035. National聽Highway聽Traffic聽Safety聽Administration, Washington,聽DC (2008)
  8. Hanowski, R.J., Olson, R.L., Hickman, J.S., Bocanegra, J.: Driver聽distraction聽in聽聽commercial聽vehicle聽operations. In: First聽International聽Conference聽on聽Driver聽Distraction聽and聽Inattention聽in聽Gothenburg, September聽28-29 (2009)
  9. Feng, L.Q., Jia, F.R., Bo, C., et al.: Analysis o f causes of rear end conflicts using naturalistic driving data collected by video drive recorders. In: Proceedings SAE Annual Congress, New York (2008)
  10. Suetoml, T., Kido, K.: Driver behavior under a collision warning system-a driving simulator study. SAE paper (2005)
  11. Sayer, J.R., Devonshire, J.M., Flanagan, C.A.: Naturalistic聽driving聽performance聽during聽secondary聽tasks. In: Proceedings聽of聽the聽Fourth聽International聽Driving聽Symposium聽on聽Human聽Factors聽in聽Driver聽Assessment, Training聽and聽Vehicle聽Design (2007)
  
• 作者单位：Chunyu Zhang (25)
  Yong Su (25)
  Jiyang Chen (26)
  Wen Wang (25) (27)
  
  25. Research Institute of Highway, M.O.T, Beijing CHENGDA Traffic Technology CO. LTD, P.R. China, Beijing, 100088, No.8 Xitucheng Rd. Haidian District
  26. Highway Administration of Liaoning Province, P.R. China, Shenyang Province, Shisan Rd. Heping District
  27. School of Economics and Business Management, BeiJing University of Aeronautics & Astronautics, China, Beijing, 100191, No.37 Xueyuan Rd. Haidian District
  

文摘

We construct a driving environment reconstruction and analysis system based on multi-sensors network onboard and some functional subsystem as well. With the data acquired, processed and stored, the real comprehensive driving environment, which includes vehicle dynamic state information, traffic environment information and driving behavior information, can be established accurately and provide what had happened in and around the vehicle. Besides, this system can also provide the researchers with additional and important information, for example traffic sign, moving object and driver gaze information. Practical results show this system is a very powerful technical framework to deep incident analysis and a quantitative evaluation measure to the effect of passive and active safety technologies, which can promote and formulate vehicle safety measures or reduce serious injuries and disabilities in addition to the reduction of fatalities and injuries in general.