پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شمارهها | 435 |
| تعداد مقالات | 5,634 |
| تعداد مشاهده مقاله | 7,427,853 |
| تعداد دریافت فایل اصل مقاله | 6,215,922 |
Investigating the effect of road characteristics on fatal crash count and crash severity; Case study: Birjand-Qayen route | ||
| AUT Journal of Civil Engineering | ||
| مقاله 8، دوره 4، شماره 2، شهریور 2020، صفحه 221-228 اصل مقاله (623.12 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajce.2019.16007.5559 | ||
| نویسندگان | ||
| Mohammad Mehdi Yaghoubi1؛ Amir Abbas Rassafi* 2؛ Nima Emrani3 | ||
| 1Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran | ||
| 2Department of Civil Engineering, Imam Khomeini International University | ||
| 3Ferdowsi University | ||
| چکیده | ||
| Motor vehicle crashes are currently among the ten major mortality factors all around the world. Iran follows a similar pattern and has a high annual rate of fatal crashes. The majority of these fatal crashes occur on rural routes, particularly on two-lane roads. In this study, the effective factors on the occurrence of accidents on Birjand-Qayen route (South Khorasan Province, Iran) is studied. In order to investigate the effects of being in two-lane segments, horizontal curves with more than 2% slope, and segments with insufficient lighting, on the fatal crash count and crash severity, standard Poisson regression model (fatal crash count per km as the dependent variable) and standard ordered logit model (severity of crashes as the dependent variable) were calibrated using the 2013-2016 data. Zero-inflated negative binomial and zero-inflated Poisson models were also applied to investigate the effect of true zero in fatal crash count modeling. Furthermore, a panel analysis of crash severity ordered logit model was carried out to consider the spatio-temporal effects. The results of the fatal crash count modeling showed that three or four-lane segments (compared to two-lane segments) reduce the number of fatal crashes, whereas curved segments with more than 2% slope (compared to straight segments) increase this number. Moreover, according to the crash severity model results, segments with sufficient lighting as well as three-lane or four-lane segments (compared to two-lane segments) reduce the severity of crashes; whereas crash severity in curved segments with more than 2% slope (compared to straight segments) is increased. | ||
| کلیدواژهها | ||
| Crash severity؛ Fatal crash count؛ Ordered logit model؛ Poisson regression model؛ Road characteristics | ||
| مراجع | ||
|
[1] L. Blincoe, T.R. Miller, E. Zaloshnja, B.A. Lawrence, The economic and societal impact of motor vehicle crashes, 2010 (Revised), in: N.H.T.S. Administration (Ed.), 2015.
[2] Investigating the causes and costs of economic and social accidents in Iran, Office of Energy, Industry and Mining, Majlis Research Center, 2013.
[3] Statistics of deaths and injuries caused by traffic accidents in 2017, Office of Public Relations and International Affairs Legal Medicine Organization of Iran, 2017.
[4] M. Saffarzadeh, S. Shabani, A. Azarmi, Accident prediction model in two-way two-lane highway curves, Bulletin of Transportation (Pajouheshnameh Haml va Naghl), 4(3) (2007) 213-221.
[5] M.M. Yaghoubi, M. Saljoghi, Identification of the accidental points of Birjand-Qayen suburban path, in: International conference on civil engineering, architecture & urban management in Iran, Tehran, Iran, 2018.
[6] N.S.S. Al-Bdairi, S. Hernandez, An empirical analysis of run-off-road injury severity crashes involving large trucks, Accident Analysis Prevention, 102 (2017) 93-100.
[7] S. Chen, T.U. Saeed, M. Alinizzi, S. Lavrenz, S. Labi, Safety sensitivity to roadway characteristics: a comparison across highway classes, Accident Analysis Prevention, 123 (2019) 39-50.
[8] A. Das, M. Abdel-Aty, A genetic programming approach to explore the crash severity on multi-lane roads, Accident Analysis Prevention, 42(2) (2010) 548-557.
[9] J. Lee, J. Chae, T. Yoon, H. Yang, Traffic accident severity analysis with rain-related factors using structural equation modeling–A case study of Seoul City, Accident Analysis Prevention, 112 (2018) 1-10.
[10] E. Zaloshnja, T.R. Miller, Cost of crashes related to road conditions, United States, 2006, in: Annals of Advances in Automotive Medicine/ Annual Scientific Conference, Association for the Advancement of Automotive Medicine, 2009, pp. 141.
[11] M.G. Karlaftis, I. Golias, Effects of road geometry and traffic volumes on rural roadway accident rates, Accident Analysis Prevention, 34(3) (2002) 357-365.
[12] S. Velmurugan, S. Padma, E. Madhu, S. Anuradha, S. Gangopadhyay, A study of factors influencing the severity of road crashes involving drunk drivers and non drunk drivers, Research in Transportation Economics, 38(1) (2013) 78-83.
[13] M. Hosseinpour, A.S. Yahaya, A.F. Sadullah, Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: Case studies from Malaysian Federal Roads, Accident Analysis Prevention, 62 (2014) 209-222.
[14] A.J. Anarkooli, M.H. Hosseinlou, Analysis of the injury severity of crashes by considering different lighting conditions on two-lane rural roads, Journal of safety research, 56 (2016) 57-65.
[15] S. Washington, M.M. Haque, J. Oh, D. Lee, Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots, Accident Analysis Prevention, 66 (2014) 136-146.
[16] L. Ma, X. Yan, C. Wei, J. Wang, Modeling the equivalent property damage only crash rate for road segments using the hurdle regression framework, Analytic Methods in Accident Research, 11 (2016) 48-61.
[17] Y. Liu, Z. Li, J. Liu, H. Patel, Vehicular crash data used to rank intersections by injury crash frequency and severity, Data in Brief, 8 (2016) 930-933.
[18] J. Ma, K.M. Kockelman, P. Damien, A baselvariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods, Accident Analysis Prevention, 40(3) (2008) 964-975.
[19] D. Chimba, T. Sando, V. Kwigizile, B. Kutela, Modeling school bus crashes using zero-inflated model, Journal of transportation statistics, 10(1) (2014) 3-11.
[20] A.J. Anarkooli, M. Hosseinpour, A. Kardar, Investigation of factors affecting the injury severity of single-vehicle rollover crashes: a random- effects generalized ordered probit model, Accident Analysis Prevention, 106 (2017) 399-410.
[21] M. Rezapour, M. Moomen, K. Ksaibati, Ordered logistic models of influencing factors on crash injury severity of single and multiple- vehicle downgrade crashes: A case study in Wyoming, Journal of Safety Research, 68 (2019) 107-118.
[22] N. Haghighi, X.C. Liu, G. Zhang, R.J. Porter, Impact of roadway geometric features on crash severity on rural two-lane highways, Accident Analysis Prevention, 111 (2018) 34-42.
[23] K. Haleem, A. Gan, Contributing factors of crash injury severity at public highway-railroad grade crossings in the US, Journal of safety research, 53 (2015) 23-29.
[24] C. Chen, G. Zhang, J. Yang, J.C. Milton, An explanatory analysis of driver injury severity in rear-end crashes using a decision table/Naïve Bayes (DTNB) hybrid classifier, Accident Analysis Prevention, 90 (2016) 95-107.
[25] A.M. Roshandeh, B.R. Agbelie, Y. Lee, Statistical modeling of total crash frequency at highway intersections, Journal of Traffic Transportation Engineering, 3(2) (2016) 166-171.
[26] R. Williams, Marginal effects for continuous variables, University of Notre Dame, 2016.
[27] T.J. Leeper, Interpreting regression results using average marginal effects with R’s margins, 2017. | ||
|
آمار تعداد مشاهده مقاله: 643 تعداد دریافت فایل اصل مقاله: 467 |
||