Abstract
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
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)
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)
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)
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)
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)
Tetsuya, N., Kenichi, Y., Horishi, N., et al.: Development and validation of a drive recorder for automobile accidents. In: Proceedings JSAE Annual Congress (2000)
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 system field operational test, data collection methods final report. Report No. DOT HS 810 035. National Highway Traffic Safety Administration, Washington, DC (2008)
Hanowski, R.J., Olson, R.L., Hickman, J.S., Bocanegra, J.: Driver distraction in commercial vehicle operations. In: First International Conference on Driver Distraction and Inattention in Gothenburg, September 28-29 (2009)
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)
Suetoml, T., Kido, K.: Driver behavior under a collision warning system-a driving simulator study. SAE paper (2005)
Sayer, J.R., Devonshire, J.M., Flanagan, C.A.: Naturalistic driving performance during secondary tasks. In: Proceedings of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, C., Su, Y., Chen, J., Wang, W. (2012). Driving Environment Reconstruction and Analysis System on Multi-sensor Network. In: Bao, Z., et al. Web-Age Information Management. WAIM 2012. Lecture Notes in Computer Science, vol 7419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33050-6_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-33050-6_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33049-0
Online ISBN: 978-3-642-33050-6
eBook Packages: Computer ScienceComputer Science (R0)