مدلسازی شدت تصادفات وسایل‌نقلیه موتوری به تفکیک گروه‌های مختلف سنی راننده با استفاده از رگرسیون لوجیت چندگانه

ناصر علوی, سید صابر; سلطانی راد, محمد; مظاهری, اکرم

doi:10.22119/jte.2022.323525.2578

مدلسازی شدت تصادفات وسایل‌نقلیه موتوری به تفکیک گروه‌های مختلف سنی راننده با استفاده از رگرسیون لوجیت چندگانه

نوع مقاله : علمی - پژوهشی

نویسندگان

¹ استادیار، دانشکده فنی و مهندسی، دانشگاه شهید باهنر کرمان، کرمان، ایران

² کارشناس ارشد راه و ترابری، دانشگاه شهید باهنر کرمان، کرمان، ایران

³ دکترای حمل‌ونقل، دانشگاه تربیت مدرس، تهران، ایران

10.22119/jte.2022.323525.2578

چکیده

موضوع نحوه ایمن‌سازی راه‌ها برای رانندگان در گروه‌های سنی مختلف به علت تغییر مداوم توزیع سنی رانندگان مهم است. با توجه به این موضوع، هدف از این مطالعه بررسی ویژگی‌های مختلف تصادف و ارائه پیشنهادات در مورد نحوهی بهبود ایمنی راه‌ها برای همه گروه‌های سنی است. این مطالعه با استفاده از سامانه داده‌های اطلاعات ایمنی راه (HSIS) عوامل موثر بر شدت آسیب تصادف وسایل‌نقلیه موتوری برای رانندگان جوان (16-25 ساله)، میانسال (26-64 ساله) و مسن (بالای 64 سال) در ایالت کالیفرنیا را از سال 2015 تا 2017 بررسی میکند. از یک مدل لوجیت چندگانه برای مدلسازی تصادفات مربوط به هر گروه سنی و ارزیابی وزن متغیرهای مختلف پیش‌بینی کننده بر شدت آسیب استفاده شد. متغیرهای پیش‌بینی کننده به چهار مشخصه راننده، راه، تصادف و محیط اطراف طبقه‌بندی شدند. نتایج نشان می‌دهد تصادف جلو به عقب احتمال مرگ‌ومیر و صدمات جانی را برای هر سه گروه سنی به میزان قابل‌توجهی افزایش می‌دهند درحالیکه آب و هوای صاف و بارانی احتمال مرگ‌ومیر و صدمات جانی را برای هر سه گروه سنی کاهش می‌دهد. همچنین نتایج نشان می‌دهد که شباهت زیادی بین عوامل پیش‌بینی‌کننده شدت تصادف برای رانندگان جوان و میانسال وجود دارد، اما رانندگان مسن‌تر در مقایسه با بقیه سایر گروه‌های سنی باید در شرایط محیطی و راه احتیاط بیشتری داشته باشند. رانندگان جوان به دلیل تجربه کم در رانندگی، مهارت‌های رانندگی خود را در طول زمان بیشتر می‌کنند، درحالیکه رانندگان میانسال به خصوص رانندگان مرد تجربه رانندگی بیشتری دارند و در نتیجه تمایل به رفتارهای پرخطر کمتری دارند. نتیجه دیگری که از این مطالعه به دست آمد این است که الگوی رفتار رانندگی در رانندگان مسن تغییرات کمتری نسبت به سایر گروه‌های سنی با صرف نظر از شرایط اطراف دارد.

کلیدواژه‌ها

20.1001.1.20086598.1402.14.4.8.9

عنوان مقاله [English]

Modeling the Severity of Motor-Vehicle Accidents by Different Age Groups of the Driver using Multinomial Logit Regression

نویسندگان [English]

Seyed Saber Naseralavi ¹
Mohammad Soltani Rad ²
Akram Mazaheri ³

¹ Assistant Professor, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

² Master of Road and Transportation Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

³ PhD of Transportation Engineering, Tarbiat Modares University, Tehran, Iran

چکیده [English]

The issue of how to make roads safer for drivers in different age groups is important due to the constant change in the age distribution of drivers. With this in mind, the purpose of this study is to investigate the different characteristics of accidents and to provide suggestions on how to improve road safety for all age groups. This study uses the Road Safety Information Database (HSIS) to determine the factors influencing the severity of motor vehicle accident injuries for young drivers (25-25 years old), middle-aged drivers (64-26 years old) and elderly drivers (over 64 years old) in California between 2015 and 2017. A multinomial logit model was used to model the accidents related to each age group and to evaluate the weight of different variables predicting the severity of the driver injury. The predictor variables were classified into four characteristics: driver, road, accident and environment. The results show that rear-end collisions significantly increase the risk of death and injury for all three age groups, while clear weather and rainy weather reduce the risk of death and injury for all three age groups. In addition, the results show that there are many similarities between the predictors of accident severity for young and middle-aged drivers, but older drivers should be more careful in environmental and road conditions compared to other age groups. Young drivers improve their driving skills over time due to less driving experience, while middle-aged drivers, especially male drivers, have more driving experience and therefore tend to engage in less risky behaviors. Another result of this study is that the driving behavior pattern of older drivers have less variation than other age groups regardless of the surrounding conditions.

کلیدواژه‌ها [English]

Accident severity analysis
multinomial logit model
Motor-Vehicle accidents
Age-based modeling

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