اولویت‌بندی عوامل مؤثر در تصادفات راه‌های روستایی استان گیلان مبتنی بر تحلیل عاملی اکتشافی و مدل رگرسیون لجستیک

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشگاه علم و صنعت ایران

2 گروه راه و ترابری، دانشکده عمران، دانشگاه علم و صنعت ایران، تهران، ایران

3 گروه راه و ترابری، دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران

چکیده

امروزه درک عوامل مؤثر در تصادفات خصوصاً در راه­های روستایی امری ضروری است. در این مطالعه به‌منظور تعیین مؤثرترین عامل بروز تصادفات، تحلیل و مدل‌سازی عوامل مؤثر در راه­های روستایی استان گیلان در سال­های 1392 تا 1397 انجام شده است. ابتدا از تحلیل فراوانی برای ارزیابی متغیرها و فراوانی آن‌ها استفاده شد. سپس از آزمون فریدمن برای اولویت‌بندی عوامل و از تحلیل عاملی اکتشافی برای تعیین مؤثرترین عامل در بروز تصادفات وسایل نقلیه استفاده شد. درنهایت برای پیش‌بینی احتمال وقوع تصادفات از مدل رگرسیون لجستیک چندگانه استفاده شد. بر اساس نتایج آزمون فریدمن، وضع آب­و­هوا، شرایط سطح راه و نوع تصادف وسیله نقلیه به ترتیب عامل‌های اول تا سوم مؤثر در تصادفات شناسایی شدند. تحلیل عاملی اکتشافی نشان داد که پنج عامل به‌عنوان اصلی­ترین عوامل در تصادفات نقش دارند که متغیرهای وضع آب­وهوا و شرایط سطح راه تحت عنوان عامل محیطی به‌عنوان اولین عامل مؤثر در تصادفات شناخته شدند. هم­چنین مدل رگرسیون لجستیک چندگانه با داشتن دقت بیشتر در پیش­بینی شدت تصادفات (7/84 درصد) نشان داد که هوای ابری، سطح راه خشک و سطح راه خیس به ترتیب بیشترین تأثیر را در رخداد تصادفات داشتند. نتایج مربوط به تحلیل حساسیت تصادفات نیز نشان داده است که رگرسیون لجستیک (با مساحت زیر نمودار 932/0) نسبت به تحلیل عاملی (با مساحت زیر نمودار 849/0) دقت بسیار بالاتری داشته که این قدرت بالای این مدل را در پیش‌بینی و ارزیابی شدت تصادفات نشان می­دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Prioritization of Effective Factors in Rural Road Accidents of Guilan Province Based on Exploratory Factor Analysis and Logistic Regression Model

نویسندگان [English]

  • Seyyed Mohsan Hosseinian 1
  • Neda Kamboozia 2
  • mahmoud ameri 3
1 Iran University of Science and Technology
2 School of Civil Engineering, Iran University of Science and Technology (IUST), 16846-13114, Tehran, I.R. Iran.
3 Iran Universty of Science and technology
چکیده [English]

Nowadays, it is necessary to understand the factors affecting accidents, especially on rural roads. In this study, in order to determine the most effective factor in the occurrence of accidents, analysis and modeling of effective factors on rural roads of Guilan province in 1392 to 1397 have been conducted. First, frequency analysis was used to evaluate the variables and their frequency. Then, Friedman test was utilized to prioritize the factors and exploratory factor analysis was used to determine the most effective factor in the occurrence of vehicle accidents. Finally, multiple logistic regression models were used to predict the probability of the occurrence of accidents. Based on Friedman test results, weather conditions, road surface conditions and the type of vehicle accident were identified as the first to third factors affecting accidents, respectively. Exploratory factor analysis showed that five factors as the main factors are involved in accidents that the variables of weather conditions and road surface conditions as an environmental factor were recognized as the first effective factor in accidents. Also, multiple logistic regression models with more accuracy in predicting the severity of accidents (84.7%) showed that cloudy weather, dry road surface and wet road surface had the highest effect on occurrence of accidents, respectively. Results of accident sensitivity analysis also showed that logistic regression (with the area under the curve 0.932) was much more accurate than factor analysis (with the area under the curve 0.849), which shows the high power of this model in predicting and evaluating of accidents severity.

کلیدواژه‌ها [English]

  • Friedman Test
  • safety
  • exploratory factor analysis
  • Rural Accidents
  • Logistic regression model
- Ahmadi Nejad, M., Shahi, J. and Sheikholeslami, A. (2006) “Modeling of Motorcycles Accidents Intensity in the City of Tehran”, Journal of Transportation Research, Vol. 3, No. 1, pp. 13-26.
 
- Bandalos, D. L. and Finney, S. J. (2010) “Exploratory and confirmatory”, The Reviewer’s Guide to Quantitative Methods in the Social Sciences, Routledge.
 
- Barua, U. and Tay, R. (2010) “Severity of urban transit bus crashes in Bangladesh”, Journal of Advanced Transportation, Vol. 44, No. 1, pp. 34-41.
 
- Casado-Sanz, N., Guirao, B. and Gálvez-Pérez, D. (2019) “Population ageing and rural road accidents: Analysis of accident severity in traffic crashes with older pedestrians on Spanish crosstown roads”, Research in Transportation Business and Management, Vol. 30, pp. 100377.
 
- Eisinga, R., Heskes, T., Pelzer, B. and Te Grotenhuis, M. (2017) “Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers”, BMC Bioinformatics, Vol. 18, No. 1, pp. 68.
 
- Garrido, R., Bastos, A., de Almeida, A. and Elvas, J. P. (2014) “Prediction of road accident severity using the ordered probit model”, Transportation Research Procedia, Vol. 3, pp. 214-223.
 
- Haleem, K., Alluri, P. and Gan, A. (2015) “Analyzing pedestrian crash injury severity at signalized and non-signalized locations”, Accident Analysis and Prevention, Vol. 81, pp. 14-23.
 
- Intini, P., Berloco, N., Colonna, P., Ranieri, V. and Ryeng, E. (2018) “Exploring the relationships between drivers’ familiarity and two-lane rural road accidents. A multi-level study”, Accident Analysis and Prevention, Vol. 111, pp. 280-296.
 
- Iran Statistical Center (2016) “Official Results of Census of Populations and Houses of Iran”.
 
- Kaiser, H. F. (1974) “An index of factorial simplicity”, Psychometrika, Vol. 39, No. 1, pp. 31-36.
 
- Kamboozia, N., Ameri, M. and Hosseinian, S. M. (2020a) “Statistical analysis and accident prediction models leading to pedestrian injuries and deaths on rural roads in Iran”, International Journal of Injury Control and Safety Promotion, pp. 1-17.
 
- Kamboozia, N., Ameri, M. and Hosseinian, S. M. (2020b) “Statistical analysis and presentation of accident prediction model leading to injuries and deaths of pedestrians in rural roads of Gilan”, Journal of Transportation Research.
 
- Kroll, C. N., Croteau, K. E. and Vogel, R. M. (2015) “Hypothesis tests for hydrologic alteration”, Journal of Hydrology, Vol. 530, pp. 117-126.
 
- Kwigizile, V., Sando, T. and Chimba, D. (2011) “Inconsistencies of ordered and unordered probability models for pedestrian injury severity”, Transportation Research Record, Vol. 2264, No. 1, pp. 110-118.
 
- Management and Planning Organization (2020), Deputy of Statistics and Information, Gilan, Iran.
 
- Montgomery, D. C., Peck, E. A. and Vining, G. G. (2012) “Introduction to linear regression analysis”, Vol. 821, John Wiley and Sons.
 
- Nahm, F. S. (2016) “Nonparametric statistical tests for the continuous data: the basic concept and the practical use”, Korean Journal of Anesthesiology, Vol. 69, No. 1, pp. 8-14.
 
- Rao, A., Han, W. and Senarathne, P. G. C. N. (2016) “A Comparison of SLAM Prediction Densities Using the Kolmogorov Smirnov Statistic”, Unmanned Systems, Vol. 4, No. 4, pp. 245-254.
 
- Ruxton, G. D., Wilkinson, D. M. and Neuhäuser, M. (2015) “Advice on testing the null hypothesis that a sample is drawn from a normal distribution”, Animal Behaviour, Vol. 107, pp. 249-252.
 
- Sheikholeslami, S., Boroujerdian, A. M., and Asadamraji, M. (2020) “A rural road accident probability model based on single-vehicle hazard properties including hazard color and mobility: a driving simulator study”, Journal of advanced transportation, Vol. 2020, pp. 1-8.
 
- Sherafati, F., Rad, E. H., Afkar, A., Gholampoor-Sigaroodi, R. and Sirusbakht, S. (2017) “Risk factors of road traffic accidents associated mortality in northern Iran; a single center experience utilizing Oaxaca blinder decomposition”, Bulletin of Emergency and Trauma, Vol. 5, No. 2, pp. 116.
 
- Shrestha, P. P. and Shrestha, K. J. (2017) “Factors associated with crash severities in built-up areas along rural highways of Nevada: A case study of 11 towns”, Journal of Traffic and Transportation Engineering (English Edition), Vol. 4, No. 1, pp. 96-102.
 
- Siskind, V., Steinhardt, D., Sheehan, M., O’Connor, T. and Hanks, H. (2011) “Risk factors for fatal crashes in rural Australia”, Accident Analysis and Prevention, Vol. 43, No. 3, pp. 1082-1088.
 
- World Health Organization (2018) “Global status report on road safety 2018”.
 
- Yasmin, S., Eluru, N. and Ukkusuri, S. V. (2014) “Alternative ordered response frameworks for examining pedestrian injury severity in New York City”, Journal of Transportation Safety and Security, Vol. 6, No. 4, pp. 275-300.
- Ye, F. and Lord, D. (2014) “Comparing three commonly used crash severity models on sample size requirements: multinomial logit, ordered probit and mixed logit models”, Analytic Methods in Accident Research, Vol. 1, pp.72-85.
 
- Young, R. K. and Liesman, J. (2007) “Estimating the relationship between measured wind speed and overturning truck crashes using a binary logit model”, Accident Analysis and Prevention, Vol. 39, No. 3, pp. 574-580.
 
- Zimmerman, K., Jinadasa, D., Maegga, B. and Guerrero, A. (2015) “Road traffic injury on rural roads in Tanzania: measuring the effectiveness of a road safety program”, Traffic Injury Prevention, Vol. 16, No. 5, pp. 456-460.