مقاله Modifying PIARC’s Linear Model of Accident Severity Index to Identify Roads” Accident Prone Spots to Rehabilitate Pavements Considering Nonlinear Effects of the Traffic Volume

توجه : به همراه فایل word این محصول فایل پاورپوینت (PowerPoint) و اسلاید های آن به صورت هدیه ارائه خواهد شد

 مقاله Modifying PIARC’s Linear Model of Accident Severity Index to Identify Roads” Accident Prone Spots to Rehabilitate Pavements Considering Nonlinear Effects of the Traffic Volume دارای ۱۲ صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

فایل ورد مقاله Modifying PIARC’s Linear Model of Accident Severity Index to Identify Roads” Accident Prone Spots to Rehabilitate Pavements Considering Nonlinear Effects of the Traffic Volume  کاملا فرمت بندی و تنظیم شده در استاندارد دانشگاه  و مراکز دولتی می باشد.

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 مقاله Modifying PIARC’s Linear Model of Accident Severity Index to Identify Roads” Accident Prone Spots to Rehabilitate Pavements Considering Nonlinear Effects of the Traffic Volume،به هیچ وجه بهم ریختگی وجود ندارد

بخشی از متن مقاله Modifying PIARC’s Linear Model of Accident Severity Index to Identify Roads” Accident Prone Spots to Rehabilitate Pavements Considering Nonlinear Effects of the Traffic Volume :

سال انتشار : ۲۰۱۶

تعداد صفحات :۱۲

Pavement rehabilitation could affect the accident severity index (ASI) since restoration measures means more safety for road users. No research or project has been carried out to identify hazard points to build a linear model based on crash severity index. One of the very popular accident severity index models used in all countries is based on linear models to rehabilitate pavements and this paper is aiming at correcting the deficiency of PIARC’s related model i.e. lack of sensitivity to changes in the traffic volume flow, to modify crash severity index (which is based on linear models) making an allowance for the nonlinear effects of traffic on eventful locations on dual carriageways. To do so, traffic volume has been chosen as the hazard criteria and, using multiple regression and statistical models, the coefficients and variables of the new model have been calculated by means of the SPSS software. This study presents the structural defects for the correction of linear models based on the accident severity (sensitive to changes in traffic volume). This research provides a linear model based on the crash severity index considering the nonlinear effects of the traffic volume to identify roads main eventful locations. Recommended that the model for a comprehensive database of accident data be built for all other roads in order to enhance the research accuracy.