كاربرد مدل‌سازي فازي در تحليل حساسيت عوامل مؤثر بر كاهش حوادث رانندگي

Fuzzy Modeling Application in Sensitivity Analysis of Factors Affecting Traffic Accidents

ﻣﺪلﻫﺎي ﭘﯿﺶﺑﯿﻨﯽ ﺗﺼﺎدﻓﺎت راﻧﻨﺪﮔﯽ ﻣﯽﺗﻮاﻧﻨﺪ ﺑﻪ درك ﻋﻠﻞ وﻗﻮع ﺗﺼـﺎدﻓﺎت ﮐﻤـﮏ ﮐـ ﺮده و وﻗـﻮع آن ﻫﺎ را در ﺷﺮاﯾﻂ ﺧﺎص ﭘﯿﺶﺑﯿﻨﯽ ﮐﻨﻨﺪ. اﯾﻦ ﻣﻄﺎﻟﻌﻪ ﺑﺎﻫﺪف اﯾﺠﺎد ﯾﮏ ﻣﺪل ﭘﯿﺶﺑﯿﻨﯽ ﺗﺼﺎدﻓﺎت ﺑﺮاي ﺑﺰرﮔﺮاه ﯾﺰد - اﻧﺎر ﺑﻪ ﻋﻨﻮان ﺑﺨﺸﯽ از ﮐﺮﯾﺪور ﺣﻤﻞ وﻧﻘﻞ ﺟﺎدهاي ﺷﻤﺎل ﺑﻪ ﺟﻨﻮب ﮐﺸﻮر ﺑﺎ اﺳـﺘﻔﺎده از روش ﻣﻨﻄـﻖ ﻓـﺎز ي اﻧﺠـﺎم و در اداﻣـﻪ، ﺗﺤﻠﯿﻞ ﺣﺴﺎﺳﯿﺖ راﻫﺒﺮدﻫﺎي ﻣﺨﺘﻠﻒ ﮐﺎﻫﺶ ﺗﺼﺎدف ﺑﺮاي ﮐﻤﮏ ﺑﻪ ﺗﺼﻤﯿﻢﮔﯿﺮﻧﺪﮔﺎن ﺑﺮاي اﺟـﺮ اي اﺻـﻼﺣﺎت ﻣﻨﺎﺳـﺐ اراﺋﻪ ﺷﺪه اﺳﺖ. روش: روش اراﺋﻪ ﺷﺪه در اﯾﻦ ﺗﺤﻘﯿﻖ اﺳﺘﻔﺎده از ﻣﻨﻄﻖ ﻓﺎزي ﺑﺮاي ﭘﯿﺶﺑﯿﻨﯽ و ﺗﺤﻠﯿﻞ ﺣﺴﺎﺳﯿﺖ ﻋﻮاﻣﻞ ﻣﺆﺛﺮ ﺑﺮ ﺗﺼـﺎدﻓﺎت ﻣﯽﺑﺎﺷﺪ ﮐﻪ ﻣﻤﮑﻦ اﺳﺖ در ﻃﻮل ﺳﺎل اﺗﻔﺎق ﺑﯿﻔﺘﺪ. دادهﻫﺎي اﯾﻦ ﺗﺤﻘﯿﻖ، ﺗﺼﺎدﻓﺎت ﺑﺰرﮔﺮاه ﯾﺰد -اﻧـﺎر در ده ﺳـﺎل اﺧﯿـﺮ و ﻣﺘﻐﯿﺮﻫﺎي ﺗﺤﻘﯿﻖ ﺷﺎﻣﻞ ﻋﺮض ﺟﺎده، ﺷﺮاﯾﻂ روﺳﺎزي ﺟﺎده، ﻣﺘﻮﺳﻂ ﺣﺠﻢ ﺗﺮاﻓﯿﮏ ﺳﺎﻋﺘﯽ، ﺳﺮﻋﺖ، ﺗﻌﺪاد ﻧﻘﺎط دﺳﺘﺮﺳـ ﯽ ﺑﻪ ﺑﺰرﮔﺮاه و وﺿﻌﯿﺖ ﻋﻼﺋﻢ راﻫﻨﻤﺎﯾﯽ و راﻧﻨﺪﮔﯽ ﻣﯽﺑﺎﺷﻨﺪ. ﺑﺎ اﻧﺠﺎم ﺗﺤﻠﯿﻞ ﺣﺴﺎﺳﯿﺖ، ﮔﺎمﻫﺎي ﻣﻨﺎﺳﺐ و اﻗﺪاﻣﺎت اﺣﺘﯿﺎﻃﯽ در ﺟﻬﺖ ﻧﯿﻞ ﺑﻪ ﮐﺎﻫﺶ ﺗﺼﺎدﻓﺎت ﭘﯿﺸﻨﻬﺎدﺷﺪه اﺳﺖ. ﯾﺎﻓﺘﻪﻫﺎ: ﯾﺎﻓﺘﻪﻫﺎي ﺗﺤﻘﯿﻖ ﻧﺸﺎن داد ﮐﻪ ﺳﯿﺴﺘﻢ ﻣﻨﻄﻖ ﻓﺎزي ﭘﯿﺸﻨﻬﺎدي، ﯾﮏ ﭘﯿﺶﺑﯿﻨـ ﯽ دﻗﯿـﻖ و ﭘﺎﯾـﺪار از ﺗﻌـﺪاد ﺗﺼـﺎدﻓﺎت راﻧﻨﺪﮔﯽ ﺑﺎ ﺿﺮﯾﺐ ﺗﻌﯿﯿﻦ ﺑﯿﺶ از 87 درﺻﺪ را ﺑﻪدﺳﺖ ﻣﯽدﻫﺪ. ﻧﺘﯿﺠﻪﮔﯿﺮي: اﺟﺮاي ﺑﺮﻧﺎﻣﻪﻫﺎي ﭘﯿﺸﻨﻬﺎدي ﮐﻮﺗـﺎه و ﺑﻠﻨﺪﻣـﺪت ﺣﺎﺻـﻞ از ﺗﺤﻠﯿـﻞ ﺣ ﺴﺎﺳـﯿﺖ ﻋﻮاﻣـﻞ ﻣـﺆﺛﺮ ﺑـﺮ ﺗﺼـﺎدﻓﺎت راﻧﻨﺪﮔﯽ، ﺑﻪ ﺗﺮﺗﯿﺐ ﺗﺼﺎدﻓﺎت را ﺑﻪ ﻣﯿﺰان 15/2 درﺻﺪ و 42/3 درﺻﺪ ﮐﺎﻫﺶ ﺧﻮاﻫﺪ داد.

Traffic accident prediction models can help to understand the causes of accidents and predict their occurrence in specific situations. The aim of this study was to create a crash prediction model for Yazd-Anar highway as part of the north-south road transport corridor using fuzzy logic method and to further analyze the sensitivity of different crash reduction strategies to help make a decision. Recipients are provided to implement appropriate corrections. Method: The method presented in this research is the use of fuzzy logic to predict and analyze the sensitivity of factors affecting accidents that may occur during the year. The data of this research are Yazd-Anar highway accidents in the last ten years and the research variables include road width, road pavement conditions, average hourly traffic volume, speed, number of access points to the highway and the status of traffic signs. By performing sensitivity analysis, appropriate steps and precautions have been suggested in order to reduce accidents. Findings: The research findings showed that the proposed fuzzy logic system provides an accurate and stable prediction of the number of traffic accidents with a coefficient of determination of more than 87%. Results: Implementation of short-term and long-term programs resulting from the sensitivity analysis of factors affecting traffic accidents will reduce accidents by 15.2% and 42.3%, respectively.