| 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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