تحلیل عوامل ترافیکی موثر بر وقوع تصادفات در نواحی ورودی تونل‌های شهری (مطالعه موردی: تونل رسالت)

ﻫﺪف از اﯾﻦ ﭘﮋوﻫﺶ، اﺳﺘﻔﺎده از ﻣﺪل ﺟﻤﻌﯽ ﺗﻌﻤﯿﻢﯾﺎﻓﺘﻪ (gam) ﺑﻪ ﻋﻨﻮان روﯾﮑﺮدی ﻧﺎﭘﺎراﻣﺘﺮی ﺑﺮای ﺷﻨﺎﺳﺎﯾﯽ ﻋﻮاﻣﻞ ﺗﺮاﻓﯿﮑﯽ ﻣﺆﺛﺮ ﺑﺮ ﻓﺮاواﻧﯽ ﺗﺼﺎدﻓﺎت در ﻧﻮاﺣﯽ دﺳﺘﺮﺳﯽ و ورودی ﺗﻮﻧﻞﻫﺎی ﺷﻬﺮی و ﻣﻘﺎﯾﺴﻪی ﻧﺘﺎﯾﺞ ﺣﺎﺻﻞ از آن ﺑﺎ ﻣﺪل ﺧﻄﯽ ﺗﻌﻤﯿﻢﯾﺎﻓﺘﻪ (glm) ﺑﻪ ﻋﻨﻮان روﯾﮑﺮدی ﭘﺎراﻣﺘﺮی اﺳﺖ. ﺳﺎﻣﺎﻧﻪ ﺗﺮددﺷﻤﺎری ﺑﻪ ﻣﻨﻈﻮر ﺟﻤﻊآوری اﻃﻼﻋﺎت و ﭘﺎراﻣﺘﺮﻫﺎی ﺗﺮاﻓﯿﮑﯽ از ﺳﻄﺢ ﻣﻌﺒﺮ ورودی ﺗﻮﻧﻞ از ﻗﺒﯿﻞ: ﺣﺠﻢ ﺳﺮﻋﺖ و درﺻﺪ اﺷﻐﺎل و ﺳﯿﺴﺘﻢ ﻧﻈﺎرت ﺗﺼﻮﯾﺮی ﻧﯿﺰ ﺑﻪ ﻣﻨﻈﻮر ﻣﺪﯾﺮﯾﺖ ﺟﺮﯾﺎن ﺗﺮاﻓﯿﮏ و ﺛﺒﺖ وﻗﺎﯾﻊ از ﺟﻤﻠﻪ ﺗﺼﺎدﻓﺎت رخ داده در داﺧﻞ ﺗﻮﻧﻞ ﻣﻮرد اﺳﺘﻔﺎده ﻗﺮارﮔﺮﻓﺘﻪ اﺳﺖ. ﭘﺲ از ﭘﺮدازش اﻃﻼﻋﺎت، از ﻣﯿﺎن اﻃﻼﻋﺎت در دﺳﺘﺮس ﺗﻌﺪاد 1047 ﺗﺼﺎدف در ﻧﻮاﺣﯽ دﺳﺘﺮﺳﯽ و ورودی ﺗﻮﻧﻞ ﺑﻪ ﻋﻨﻮان ﻣﺘﻐﯿﺮ واﺑﺴﺘﻪ و ﺳﻪ ﻣﺘﻐﯿﺮ ﻟﮕﺎرﯾﺘﻢ ﺣﺠﻢ ﺗﺮاﻓﯿﮏ، ﻓﺮاواﻧﯽ وﺳﺎﯾﻞﻧﻘﻠﯿﻪ ﺳﻨﮕﯿﻦ (درﺻﺪ) و اﺧﺘﻼف ﺳﺮﻋﺖ از ﻣﺤﺪودﯾﺖ ﺳﺮﻋﺖ ﺑﺰرﮔﺮاه ﺑﻪﻋﻨﻮان ﻣﺘﻐﯿﺮﻫﺎی ﻣﺴﺘﻘﻞ ﻧﻬﺎﯾﯽ ﺑﺮای ﻓﺮآﯾﻨﺪ ﻣﺪلﺳﺎزی اﻧﺘﺨﺎب ﺷﺪﻧﺪ. ﺑﺮ اﺳﺎس ﻧﺘﺎﯾﺞ ﻣﺪل ﺧﻄﯽ ﺗﻌﻤﯿﻢ ﯾﺎﻓﺘﻪ، اﺛﺮ ﺧﻄﯽ ﻣﺘﻐﯿﺮﻫﺎی ﻟﮕﺎرﯾﺘﻢ ﺣﺠﻢ روزاﻧﻪ، ﻓﺮاواﻧﯽ وﺳﺎﯾﻞﻧﻘﻠﯿﻪ ﺳﻨﮕﯿﻦ و اﺧﺘﻼف ﻣﯿﺎﻧﮕﯿﻦ ﺳﺮﻋﺖ روزاﻧﻪ وﺳﺎﯾﻞﻧﻘﻠﯿﻪ ﻋﺒﻮری از ﺗﻮﻧﻞ ﻧﺴﺒﺖ ﺑﻪ ﻣﺤﺪودﯾﺖ ﺳﺮﻋﺖ ﺑﺰرگراه در ﻓﺮاواﻧﯽ ﺗﺼﺎدﻓﺎت ﻧﻮاﺣﯽ دﺳﺘﺮﺳﯽ و ورودی ﺗﻮﻧﻞ ﻣﻌﻨﯽدار ﺑﺪﺳﺖ آﻣﺪ. ﺿﺮﯾﺐ ﺧﻮﺑﯽ ﺑﺮازش ﺑﺎﻻﺗﺮ (0/099) و ﻣﻌﯿﺎر اﻃﻼﻋﺎﺗﯽ آﮐﺎﺋﯿﮏ ﭘﺎﯾﯿﻦ ﺗﺮ (3823) ﻣﺪل ﺟﻤﻌﯽ ﺗﻌﻤﯿﻢﯾﺎﻓﺘﻪ ﺑﺮﺗﺮی اﯾﻦ ﻣﺪل را در ﻣﻘﺎﯾﺴﻪ ﺑﺎ ﻣﺪل ﺧﻄﯽ ﺗﻌﻤﯿﻢﯾﺎﻓﺘﻪ ﻧﺸﺎن داد . ﻧﻮﺳﺎﻧﺎت ﺳﺮﻋﺖ اﯾﺠﺎدﺷﺪه ﻫﻨﮕﺎم ورود ﺑﻪ ﺗﻮﻧﻞ ﻫﺎ ﺑﺮای ﻫﻤﺎﻫﻨﮕﯽ ﺑﺎ ﺷﺮاﯾﻂ ﻣﺤﯿﻄﯽ ﺗﻮﻧﻞ ﻣﺎﻧﻨﺪ ﺷﺮاﯾﻂ روﺷﻨﺎﯾﯽ، ﻣﯽﺗﻮاﻧﺪ ﯾﮑﯽ از ﻋﻮاﻣﻠﯽ ﺑﺎﺷﺪ ﮐﻪ ﺗﺄﺛﯿﺮ ﻣﺨﺮﺑﯽ ﺑﺮ اﯾﻤﻨﯽ ﺗﺮاﻓﯿﮏ ﻋﺒﻮری از ﺗﻮﻧﻞ دارد.

Analysis of Traffic Factors Affecting the Accidents in the Urban Tunnel Entry Areas (Case Study: Resalat Tunnel)

Urban tunnels are one of the major infrastructures in transportation networks of metropolitan cities. Owing to the enclosed space of tunnels, the safety of through passage is essential. Identify factors affecting the frequency of accidents in urban tunnels can be useful in preventing and reducing related casualties. In this research, we try to determine the factors affecting a number of accidents by comparing the generalized linear model and the generalized additive model. The data of Resalat tunnel comes from Tehranchr('39')s urban tunnels control and management centre, which includes the daily volume variables, the percentage of heavy vehicles, the difference between the average speed of passing vehicles from the tunnel and the speed limit of the highway as independent variables, and the number of accidents per day during the period 2010 to 2012 as dependent variable. In this research, R software programs are used respectively for fitting a generalized linear and generalized additive model. Based on the results of generalized linear and generalized additive models, the percentage of heavy vehicles and the difference between the average speed of passing vehicles from the tunnel and the speed limit of the highway are significantly and positively related to the frequency of accidents in the access and entrance areas of the tunnel. The logarithm of daily traffic volume is not meaningful in the generalized additive model, in contrast to the generalized linear model. Therefore, identifying the factors affecting the frequency of accidents in urban tunnels by using advanced statistical models will greatly help to develop effective measures in improving the safety of tunnels. Urban tunnels are one of the major infrastructures in transportation networks of metropolitan cities. Owing to the enclosed space of tunnels, the safety of through passage is essential. Identify factors affecting the frequency of accidents in urban tunnels can be useful in preventing and reducing related casualties. In this research, we try to determine the factors affecting a number of accidents by comparing the generalized linear model and the generalized additive model. The data of Resalat tunnel comes from Tehranchr('39')s urban tunnels control and management centre, which includes the daily volume variables, the percentage of heavy vehicles, the difference between the average speed of passing vehicles from the tunnel and the speed limit of the highway as independent variables, and the number of accidents per day during the period 2010 to 2012 as dependent variable. In this research, R software programs are used respectively for fitting a generalized linear and generalized additive model. Based on the results of generalized linear and generalized additive models, the percentage of heavy vehicles and the difference between the average speed of passing vehicles from the tunnel and the speed limit of the highway are significantly and positively related to the frequency of accidents in the access and entrance areas of the tunnel. The logarithm of daily traffic volume is not meaningful in the generalized additive model, in contrast to the generalized linear model. Therefore, identifying the factors affecting the frequency of accidents in urban tunnels by using advanced statistical models will greatly help to develop effective measures in improving the safety of tunnels.