Abstract:
The remarkable advancements in the field of Intelligent Transportation System (ITS)
over the past two decades have promoted several studies on improving safety aspects
of acess controlled roads. As many of the expressways in the developed world are
instrumented to generate adequate amount of data on the traffic condition in realtime,
it is possible to monitor traffic condition more closely and identify any
anomaly that can evolve into a hazardous traffic condition. The result of which leads
to the formation of real-time crash prediction model.
In present context ensuring pro-active road safety management plays a vital role in
transportation modeling. To design a pro-active road safety management system, it is
important to be able to devise a way to bring the hazardous traffic condition back to
normal. In the past several studies have taken place where micro-simulation or
driving simulator based approaches were adopted to achieve that. For the purpose of
this study, a micro-simulation based approach was chosen. It is to be noted that
driving simulator could capture individual driving behavior at a greater depth but as
use of it involves a great deal of time as well as it depends on the respondents, it was
avoided.
Micro-simulation approach is a profound tool used by researchers to determine and
analyze traffic characteristics. Micro-simulation approach gives access to car
following as well as lane changing behavior of individual vehicle and allows
analyzing their interactions by changing the parameters. Existing studies provided
very little insight into how to simulate hazardous traffic condition. So, in this study,
a detailed and step-by-step explanation on how to simulate hazardous traffic
condition has been incorporated.
CUBE Dynasim is a micro-simulation software developed by CITILABS which was
used in this study. In CUBE Dynasim the normal traffic condition was created by
using aggregated flow data obtained from Route 3 and Route 4 of Tokyo
Metropolitan Expressway. The values of the parameters were altered to create
hazardous traffic flow condition.
Best possible result was obtained by changing the values of car-following maximum
threshold and mean of threshold value for car following rules. Again, in case of lane
Abstract
v
changing behavior changing of heavy vehicle threshold, light vehicle average time,
light vehicle minimum time, light vehicle maximum time, light vehicle standard
deviation, light vehicle minimum distance, heavy vehicle average time, heavy
vehicle minimum time, heavy vehicle maximum time, heavy vehicle standard
deviation, heavy vehicle minimum distance reflected best result. The outcome of the
study was verified by comparing the field traffic flow variable data with that of the
simulated data.
Description:
Supervised by
Moinul Hossain
Assistant Professor ,
Department of Civil and Environmental Engineering (CEE)
Islamic University of Technology (IUT)
Board Bazar, Gazipur, Bangladesh.