Identification of Critical Factors for Crash Duration with Consideration of Unobserved Heterogeneity

Younshik Chung; Sangsu Kim

doi:10.7470/jkst.2020.38.6.536

All Issue

2020 Vol.38, Issue 6 Preview Page

Article

Identification of Critical Factors for Crash Duration with Consideration of Unobserved Heterogeneity 비관측 이질성을 고려한 고속도로 교통사고 지속시간 영향인자 분석

31 December 2020. pp. 536-546

PDF XML

Abstract

To reduce non-recurrent congestion, it is necessary to understand of crash duration and its causal factors. Therefore, there have been various efforts to develop crash duration models since 1980s. Specifically, regression type models based on survival analysis have mainly been applied to this area. However, most of them have applied general survival analysis models, in which durations with the same value of the covariates are assumed to have the same distribution. Unlike previous studies, the purpose of this study is to develop a crash duration with the consideration of unobserved heterogeneity. To carry out this purpose, we used a 1-year (2018) crash data set collected from the entire Korean freeway system, and estimated a frailty model for crash duration. As a result, 11 variables were statistically significant. Of these, eight variables exhibited an increasing duration: crashes that occurred in tunnel, crashes that occurred in section without street lighting, crashes with trailer-truck or specially equipped vehicle, crashes involved in completely damage vehicle, vehicle status was in off-road, rollover, or fire after crash. Conversely, crashes in the vicinity of tollgate, crashes including property damage only and crashes reported by freeway service patrol contributed to decreasing crash duration.

Keywords

crash duration

frailty model

freeway crash

survival analysis

unobserved heterogeneity

비반복적 발생 혼잡을 감소시키기 위해서는 사고 지속시간에 대한 이해와 사고 지속시간에 영향을 미치는 인자에 대한 파악이 필요하다. 이를 위해 1980년대 이래 다양한 연구가 수행되어왔다. 특히, 생존분석 기반 회귀분석을 적용한 연구가 주류를 이루고 있으나, 대부분의 연구에서는 비관측 이질성을 고려하지 않고 모형을 구축했다. 따라서 본 연구의 주요 목적은 비관측 이질성(unobserved heterogeneity)의 영향력을 고려한 고속도로 사고 지속시간 모형을 구축하는 것이다. 분석을 위해 2018년 전국 고속도로에서 발생한 교통사고 자료가 활용되었으며, 프레일티(frailty) 모형 기반 사고 지속시간 모형을 구축하였다. 분석결과, 11개의 변수가 사고 지 속시간에 영향을 미치는 것으로 나타났으며, 사고 지속시간을 증가시키는 요인은 터널에서 발생한 사고, 트레일러 및 특수차량의 사고, 차량이 완파된 사고, 도로이탈 추락이 발생한 사고, 전도 및 화재가 발생한 사고, 조명이 없는 도로구간에서 발생한 사고로 나타났다. 반면, 톨게이트에서 발생한 사고, 대물피해가 발생한 사고, 고속도로 순찰대의 순찰중 제보된 사고는 사고 지속시간을 감소시키는 요인으로 나타났다.

키워드

사고 지속시간

프레일티 모형

고속도로 교통사고

생존분석

비관측 이질성

References

Akaike H. (1974), A New Look at the Statistical Model Identification, IEEE Transactions on Automatic Control, 19(6), 716-723. 10.1109/TAC.1974.1100705

Al Kaabi A. M. S., Dissanayake D., Bird R. (2011), Analyzing Clearance Time of Urban Traffic Accidents in Abu Dhabi, United Arab Emirates, with Hazard-based Duration Modeling Method, Transportation Research Record, 2229(1), 46-54. 10.3141/2229-06

Al Kaabi A. M. S., Dissanayake D., Bird R. (2012), Response Time of Highway Traffic Accidents in Abu Dhabi: Investigation with Hazard-based Duration Models, Transportation Research Record, 2278, (1), 95-103. 10.3141/2278-11

Chung Y. (2010), Development of an Accident Duration Prediction Model on the Korean Freeway Systems, Accident Analysis & Prevention, 42(1), 282-289. 10.1016/j.aap.2009.08.00519887169

Chung Y. (2011), Assessment of Non-recurrent Traffic Congestion Caused by Freeway Work Zones and its Statistical Analysis with Unobserved Heterogeneity, Transport Policy, 18(4), 587-594. 10.1016/j.tranpol.2011.02.003

Chung Y. (2017), Identification of Critical Factors for Non-recurrent Congestion Induced by Urban Freeway Crashes and Its Mitigating Strategies, Sustainability, 9(12), 2331. 10.3390/su9122331

Chung Y., Kim S. J. (2017), Crash Clearance Time Analysis of Korean Freeway Systems using a Cox Model, Journal of the Korean Society of Civil Engineers, 37(6), 1017-1023.

Chung Y., Song S., Choi K. (2007), A Prediction Model on Freeway Accident Duration using AFT Survival Analysis, J. Korean Soc. Transp., 25(5), Korean Society of Transportation, 135-148.

Chung Y., Recker W. W. (2015), Frailty Models for the Estimation of Spatiotemporally Maximum Congested Impact Information on FreewayAaccidents, IEEE Transactions on Intelligent Transportation Systems, 16(4), 2104-2112. 10.1109/TITS.2015.2394798

Chung Y., Walubita L. F., Choi K. (2010), Modeling Accident Duration and Its Mitigation Strategies on South Korean Freeway Systems, Transportation Research Record, 2178(1), 49-57. 10.3141/2178-06

Chung Y.-S., Chiou Y.-C., Lin C.-H. (2015), Simultaneous Equation Modeling of Freeway Accident Duration and Lanes Blocked, Analytic methods in accident research, 7, 16-28. 10.1016/j.amar.2015.04.003

Cleves M., Gould W., Gould W. W., Gutierrez R., Marchenko Y. (2008), An Introduction to Survival Analysis using stata,Stata press.

Golob T. F., Recker W. W., Leonard J. D. (1987), An Analysis of the Severity and Incident Duration of Truck-involved Freeway Accidents, Accident Analysis & Prevention, 19(5), 375-395. 10.1016/0001-4575(87)90023-6

Hensher D. A., Mannering F. L. (1994), Hazard‐based Duration Models and Their Application to Transport Analysis, Transport Reviews, 14(1), 63-82. 10.1080/01441649408716866

Hojati A. T., Ferreira L., Washington S., Charles P. (2013), Hazard Based Models for Freeway Traffic Incident Duration, Accident Analysis & Prevention, 52, 171-181. 10.1016/j.aap.2012.12.03723333698

Jones B., Janssen L., Mannering F. (1991), Analysis of the Frequency and Duration of Freeway Accidents in Seattle, Accident Analysis & Prevention, 23(4), 239-255. 10.1016/0001-4575(91)90003-N

Khattak A. J., Schofer J. L., Wang M.-H. (1995), A Simple Time Sequential Procedure for Predicting Freeway Incident Duration, Journal of Intelligent Transportation Systems, 2(2), 113-138. 10.1080/10248079508903820

Kim H. W., Lee Y. I. (2015), Developing Incident Response Time Prediction Model for Highway by KNN Algorithm, The 73rd Conference of KST, Korean Society of Transportation, 197-202.

Lee S. B., Chang H. H., Lee Y. I. (2015), Development Hybrid Model for Incident Clearance Time Prediction in Highway, The 73rd Conference of KST, Korean Society of Transportation, 281-286.

Liu Z., Wu H., Li R. (2020), Effects of the Penalty Mechanism Against Traffic Violations in China: A Joint Frailty Model of Recurrent Violations and a Terminal Accident, Accident Analysis & Prevention, 141, 105547. 10.1016/j.aap.2020.10554732334154

Nam D., Mannering F. (2000), An Exploratory Hazard-based Analysis of Highway Incident Duration, Transportation Research Part A: Policy and Practice, 34(2), 85-102. 10.1016/S0965-8564(98)00065-2

Ozbay K., Noyan N. (2006), Estimation of Incident Clearance Times using Bayesian Networks Approach, Accident Analysis & Prevention, 38(3), 542-555. 10.1016/j.aap.2005.11.01216426557

Shin C. H. (2004), Development of Decision-trees for Freeway Incident Duration Prediction, Journal of the Korean Society of Civil Engineers, 24(5d), 681-689.

Shin C. H., Kim J. H. (2002), Development of Freeway Incident Duration Prediction Models, J. Korean Soc. Transp., 20(3), Korean Society of Transportation, 17-30.

Smith K., Smith B. L. (2002), Forecasting the Clearance Time of Freeway Accidents.

TRB (1994), Highway Capacity Manual: Special report 209, Transportation Research Board, National Research Council, Washington, DC.

Vaupel J. W., Manton K. G., Stallard E. (1979), The Impact of Heterogeneity in Individual Frailty on the Dynamics of Mortality, Demography, 16(3), 439-454. 10.2307/2061224510638

Washington S., Karlaftis M. G., Mannering F., Anastasopoulos P. (2020), Statistical and Econometric Methods for Transportation Data Analysis CRC press. 10.1201/9780429244018

Information

Publisher :Korean Society of Transportation
Publisher(Ko) :대한교통학회
Journal Title :Journal of Korean Society of Transportation
Journal Title(Ko) :대한교통학회지
Volume : 38
No :6
Pages :536-546
Received Date : 2020-09-07
Revised Date : 2020-10-04
Accepted Date : 2020-10-11
DOI :https://doi.org/10.7470/jkst.2020.38.6.536

Journal of Korean Society of Transportation ISSN:1229-1366(Print) 2234-4217(Online) 대한교통학회지

All Issue