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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2012(Vol.4, Issue:22)
Article Information:

The Evaluation of Lane-Changing Behavior in Urban Traffic Stream with Fuzzy Clustering Method

Ali Abdi, Hossein Mobasheri and Mir Pouya Naseri Alavi
Corresponding Author:  Hossein Mobasheri 
Submitted: March 30, 2012
Accepted: April 30, 2012
Published: November 15, 2012
Abstract:
We present a method for The Evaluation of Lane-Changing Behavior in Urban Traffic Stream with Fuzzy Clustering Method. The trends for drivers Lane-Changing with regard to remarkable effects in traffic are regarded as a major variable in traffic engineering. As a result, various algorithms have presented most models of Lane-Changing developed by means of lane information and the manner of vehicle movement mainly obtained from images process not much attention is given to the characteristics of driver. Lane change divided into two parts the first one are compulsory lane including lane change to turn left or turn right. The second type of change is optional and lane change to improve driving condition. A low speed car is a good example, in this study, through focused group discussion method, drivers information can be obtained so that driver’s personality traits are taken into consideration. Then drivers are divided into four groups by means of Algorithm clusters. The four Algorithms suggest that phase typed cluster is a more suitable method for drivers classification based on Lane-Changing. Through notarization of different type of scenarios of lane change in Iran following results released. The percentage of drivers for each group is 17/5, 35, 20 and 27/ %, respectively.

Key words:  Focus group discussions , fuzzy clustering, lane-changing, urban traffic, , ,
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Cite this Reference:
Ali Abdi, Hossein Mobasheri and Mir Pouya Naseri Alavi, . The Evaluation of Lane-Changing Behavior in Urban Traffic Stream with Fuzzy Clustering Method. Research Journal of Applied Sciences, Engineering and Technology, (22): 4701-4710.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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