摘要(英) |
Since the development of automobile industry technology and production skills, the
production rate of automobiles raises dramatically. Moreover, the number of vehicles
continuously increases in the world. In 21th century, according to the OICA (Organization
International des Constructeurs d’’Automobiles) the number of new vehicles over 50 million
every year. There are more over 75 million new vehicles produced in 2010 and 2011. Since
the cars getting more and more, there are more and more traffic problems happened. Traffic
accidents and traffic congestion become many countries’ thorny problem.
With the development of computer and communication technology, each country attends
to develop intelligent transportation systems (ITS), which combine electrics, communication,
computer, control and sensor techniques to apply to many kinds of transportation system. ITS
can improve the traffic safety and traffic service through the real-time information
transportation. Vehicular Ad hoc network (VANETs) is one important technique of the
intelligent transportation systems. Vehicular Ad hoc networks utilize the networks composed
by OBU (On Board Unit) and RSU(Road Side Unit) to take communication between cars.
Therefore, the Vehicular Ad hoc network skills could expand more networks application
which likes safety message dissemination and weather forecasting and real-time situation of
vehicles. To improve the traffic safety and decrease the traffic accidents is the most important
target of Intelligent Transportation System. According to the statistics of “why traffic accident
happen?” from Ministry of Transportation Communications from 2008 to 2011, we find out
that the driver is the critical reason; it takes account for the proportion 96 percentage. Driver
factors include speeding and drunk driving…etc.
This paper proposes a prevention of dangerous driving scheme for on-road vehicle use
VANET to exchange messages with each other to determine whether a vehicle dangerous and
to give the vehicles suggested strategy to prevent possible dangerous situations. Finally, use
NCTUns 6.0 simulator to simulate several experiments, before and after this mechanism for
the purposes of impact analysis. By the result of simulation, it improves 42.95% for collisions,
it improves 43.02% for violation of safety distance, it improves 14.02% for violation of speed
variance, it improves 42.71% for the number of lane change and it improves 35.56% for
violation of lane change frequency. This scheme can reduce vehicle traffic accidents, and
maintain road traffic safety.
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參考文獻 |
[1] Organisation Internationale des Constructeurs d’’Automobiles (OICA),
http://www.oica.net/
[2] Organisation for Economic Co-operation and Development (OECD),
http://www.oecd.org
[3] K. Suriyapaibonwattana, “An Effective Safety Alert Broadcast Algorithm for VANET,”
Proceedings of IEEE International Symposium on Communications and Information
Technologies, pp.247-250, 2008.
[4] K. Suriyapaibonwattana, “An adaptive alert message dissemination protocol for VANET
to improve road safety,” Proceedings of IEEE International Conference on Fuzzy
Systems, pp.1639-1644, 2009.
[5] The Research and Innovative Technology Administration (RITA),
http://www.rita.dot.gov/
[6] ISO - International Organization for Standardization, http://www.iso.org/
[7] ISO 15623, Transport Information and Control Systems-Forward Vehicle Collision
Warning Systems-Performance Requirements and Test Procedures
[8] Smart Motorist, http://www.smartmotorist.com/traffic-and-safety-guideline/maintain-asafe-
following-distance-the-3-second-rule.html
[9] World Health Organization (WHO), http:// www.who.int/
[10] The Australian Transport Safety Bureau (ATSB), http://www.atsb.gov.au/
[11] W. Nelson, “Continuous-curvature paths for autonomous vehicles,” Proceedings of
IEEE International Conference on Robotics and Automation, vol. 3, pp.1260-1264, 1989.
[12] T. Shamir, “How should an autonomous vehicle overtake a slower moving vehicle:
design and analysis of an optimal
[13] L. S. Jin, W.P. Fang, Y. N. Zhang, S. B. Yang, H. J. Hou, “Research on safety lane
change model of driver assistant system on highway,” Proceedings of IEEE
International Conference on Intelligent Vehicles Symposium, pp.1051-1, 2009.
[14] G. Xu, L. Liu, Z. Song, Y. Ou, “Generating lane-change trajectories using the dynamic
model of driving behavior,” Proceedings of IEEE International Conference on
Information and Automation (ICIA), pp.464-469, 2011.
[15] E. Tian, “Driver characteristics in the lane change process,” Proceedings of IEEE
International Conference on Remote Sensing, Environment and Transportation
Engineering (RSETE) , pp.3093-3096, 2011.
[16] Y. Kanayama, “Smooth local path planning for autonomous vehicles,” Proceedings of
IEEE International Conference on Robotics and Automation, vol 3,pp.1265-1270, 1989.
[17] T. Umedu, K. Isu, T. Higashino, C.K. Toh, “An Intervehicular-Communication Protocol
for Distributed Detection of Dangerous Vehicles,” IEEE Transactions on Vehicular
Technology, vol 59, Issue 2, pp.627-637, 2010.
[18] J. M. Utts, and R.F. Heckard, Statistical Ideas and Methods, Cengage Learning, Jan. 26,
2005.
[19] Normal distribution, http://en.wikipedia.org/wiki/Normal_distribution
[20] M. Sakairi, “Water-Cluster-Detecting Breath Sensor and Applications in Cars for
Detecting Drunk or Drowsy Driving,” IEEE Sensors Journal, vol 12, Issue 5, pp.1078-
1083, 2012
[21] J. Teng, X. Bai, Z. Shen, D. Xuan, “Mobile Phone Based Drunk Driving Detection,”
Proceedings of IEEE Pervasive Computing Technologies for Healthcare, pp.1-8, 2010
[22] The American Academy of Dental Sleep Medicine (AADSM),
http://www.aadsm.org/pdfs/drowsydrivingfacts.pdf
[23] NCTUns 6.0 Network Simulator and Emulator, http://nsl.csie.nctu.edu.tw/nctuns.html
[24] S.Y. Wang and C.L. Chou, “NCTUns Tool for Wireless Vehicular Communication
Network Researches,” Simulation Modelling Practice and Theory, vol. 17, No. 7, pp.
1211-1226, Aug. 2009.
[25] S.Y. Wang, C.L. Chou, C. C. Lin, and C.H. Huang, “The Protocol Developer Manual for
the NCTUns 6.0 Network Simulator and Emulator,”
http://nsl10.csie.nctu.edu.tw/support/documentation/DeveloperManual.pdf
[26] S.Y. Wang, C.L. Chou, and C.C. Lin, “The GUI User Manual for the NCTUns 6.0
Network Simulator and Emulator,” http://nsl10.csie.nctu.edu.tw/support/
documentation/GUIManual.pdf
[27] Transportation Research Institute Oregon State University,” Stopping Sight Distance
And Decision Sight Distance,”
http://www.oregon.gov/ODOT/HWY/ACCESSMGT/docs/StopDist.pdf
[28] Collision avoidance system, http://en.wikipedia.org/wiki/Collision_avoidance_system
[29] 內政部警政署, http://www.npa.gov.tw/
[30] 中華智慧型運輸系統協會, http://www.its-taiwan.org.tw/
[31] 中華民國交通部, http://www.motc.gov.tw
[32] 中華民國內政部, http://www.moi.gov.tw/
[33] 交通部臺灣區國道高速公路局, http://www.freeway.gov.tw
[34] 交通部運輸研究所, “駕駛人行為反應之研究—酒醉駕車對駕駛行為之分析研究”
http://www.iot.gov.tw/
[35] 朱禮伶,”應用駕駛模擬器探討酒後駕駛行為反應之研究,” 國立成功大學交通管理科
學系碩士班碩士論文, 2009.
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