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Prioritization of suburban accident factor based on analytical network process دارای 17 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

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توجه : در صورت  مشاهده  بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل ورد می باشد و در فایل اصلی Prioritization of suburban accident factor based on analytical network process،به هیچ وجه بهم ریختگی وجود ندارد

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بخشی از متن Prioritization of suburban accident factor based on analytical network process :

سال انتشار : 1394

نام کنفرانس یا همایش : پانزدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک

تعداد صفحات : 17

چکیده مقاله:

 

Used as a criterion measuring the development of the countries, transportation plays the crucial role in economic infrastructure. The safety management of transportation systemleads to decrease in a number of traffic accident occurrences lifting the standards specified for a transportation network. Understanding the traffic accident processes and relatedreasons are of the initial steps in controlling the crashes. Traffic accidents as the randomand multi-reason phenomena root in the lack of equilibrium between the system’s components. The source of the accidents is divided into 3 groups; namely, human based,environmental based and traffic based factors. Human factors are more effective in the occurrence of traffic accidents compared to others. Also, other factors may affect the human factors as well. Hence, due to the complex nature of traffic accidents, Multi-Criteria Decision-making (MCDM) methods can be considered. In this study, analytical network process (ANP) was utilized to evaluate the interaction of human, traffic and roadrelated parameters in occurrence of traffic accidents. Also, statistic analysis was used in decision making components directly. Sub-urban accidents data in the length of 945 km of Hamedan province road network in three-year period from 2011 to 2013 were consideredas a case study. As a result, In comparison to other factors, road factors had higher priority. That is, Factors such as curvature and slope were more effective than human characteristics. Furthermore, it was concluded that, Condition curvature (0-100) degree per kilometer and slope (0-3%) had higher risk of accidents.

 

 

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