Novel Crash Surrogate Measure for Freeways
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 8
Abstract
In this paper, a disturbance-based methodology was proposed to represent the safety level of a car-following scenario. According to the probabilistic causal model, the following vehicles always take evasive actions to avoid a collision in the crash mechanism. In this study, the probabilistic model is modified to evaluate the maximum disturbance a car-following scenario can accommodate corresponding to the maximum evasive action taken by the following vehicle. This paper aims to investigate the safety level of a car-following scenario by estimating its capability index on accommodating disturbance. The surrogate measure, Disturbance Accommodate Index (DAI), is thus proposed to represent the stability of a car-following scenario by measuring its maximum capability on accommodating disturbance. Further, a case study is conducted to evaluate the performance of DAI by using the traffic and crash data provided by the Department of Transport and Main Roads in Queensland. The results show that the DAI outperforms the other crash surrogate measures (e.g., Aggregated Crash Index, Time to Collision, and Proportion of Stopping Distance) in representing rear-end crash risk, followed by the discussion.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
This research is supported by the DTMR in Queensland on providing the traffic and crash data. The authors are indebted to the Editor in Chief and all anonymous reviewers for their insightful comments that significantly improved this work.
References
AASHTO. 2004. American association of state highway and transportation officials. Washington, DC: AASHTO.
Allen, B. L., B. T. Shin, and D. J. Cooper. 1978. “Analysis of traffic conflicts and collision.” Transp. Res. Rec. 667: 67–74.
Archer, J., (2005). Indicators for traffic safety assessment and prediction and their application in micro-simulation modeling study of urban and suburban intersections. Stockholm, Bonsalla: Sweden Royal Institute of Technology.
Benekohal, R. F. 1991. “Procedure for validation of microscopic traffic flow simulation models.” Transp. Res. Rec. 1320: 190–202.
Bham, G. H., and R. F. Benekohal. 2004. “A high fidelity model based on cellular automata and car-following concepts.” Transp. Res. Part C 12 (1): 1–32. https://doi.org/10.1016/j.trc.2002.05.001.
Brill, E. 1972. “A car-following model relating reaction times and temporal headways to accident frequency.” Transp. Sci. 6 (4): 343–353. https://doi.org/10.1287/trsc.6.4.343.
Caflisch, R. E. 1998. Monte Carlo and quasi-MonteCarlo methods. Acta Numerica 7, 1–49. Cambridge, UK: Cambridge University Press.
Chin, H. C., and S. T. Quek. 1997. “Measurement of traffic conflicts.” Saf. Sci. 26 (3): 169–185. https://doi.org/10.1016/S0925-7535(97)00041-6.
Cooper, F., and N. Ferguson. 1976. “Traffic studies at t-junctions–a conflict simulation model.” Traffic Eng. Control 17 (7): 306–309.
Cunto, F., D. Duong, and F. Saccomanno. 2009. “Comparision of simulated freeway safety performance with observed crashes.” Transp. Res. Rec. 2103 (1): 88–97. https://doi.org/10.3141/2103-11.
Cunto, F., and F. F. Saccomanno. 2008. “Calibration and validation of simulated vehicle safety performance at signalized intersections.” Accid. Anal. Prev. 40 (3): 1171–1179. https://doi.org/10.1016/j.aap.2008.01.003.
Davis, G., J. Hourdos, H. Xiong, and I. Chatterjee. 2011. “Outline of a causal model of traffic conflicts and crashes.” Accid. Anal. Prev. 43 (6): 1907–1919. https://doi.org/10.1016/j.aap.2011.05.001.
Dong, C., Q. Dong, B. Huang, and W. Hu. 2017. “Estimating factors contributing to frequency and severity of large truck–involved crashes.” J. Transp. Eng., Part A: Syst. 143 (8): 04017032. https://doi.org/10.1061/JTEPBS.0000060.
Dowling, R., A. Skabardnis, and V. Alexiadis. 2004. Traffic analysis toolbox. Volume III: Guidelines for applying traffic microsimulation software. Washington, DC: FHWA.
Farah, H., S. Bekhor, and A. Polus. 2009. “Risk evaluation by modeling of passing behavior on two-lane rural highways.” Accid. Anal. Prev. 41 (4): 887–894. https://doi.org/10.1016/j.aap.2009.05.006.
Guido, G., F. Saccomanno, A. Vitale, V. Astarita, and D. Festa. 2011. “Comparing safety performance measures obtained from video capture data.” J. Transp. Eng. 137 (7): 481–491. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000230.
Habtemichael, F., and L. Picado-Santos. 2014. “Crash risk evaluation of aggressive driving on motorways: Microscopic traffic simulation approach.” Transp. Res. Part F 23 (Mar): 101–112. https://doi.org/10.1016/j.trf.2013.12.022.
Harb, R., E. Radwan, X. Yan, A. Pande, and M. Abdel-Aty. 2008. “Freeway work-zone crash analysis and risk identification using multiple and conditional logistic regression.” J. Transp. Eng. 134 (5): 203–214. https://doi.org/10.1061/(ASCE)0733-947X(2008)134:5(203).
Hauer, E. 2004. “Statistical road safety modeling.” Transp. Res. Rec. 1897 (1): 81–87. https://doi.org/10.3141/1897-11.
Hayward, J. C. 1972. “Near miss determination through use of a scale of danger.” Transp. Res. Rec. 384: 24–34.
Holm, P., D. Tomich, J. Sloboden, and C. Lowranc. 2007. Traffic analysis toolbox volume IV: Guidelines for applying CORSIM microsimulation modelling software. Washington, DC: FHWA.
Huang, F., P. Liu, H. Yu, and W. Wang. 2013. “Identifying if VISSIM simulation model and SSAM provide reasonable estimates for field measured traffic conflicts at signalized interactions.” Accid. Anal. Prev. 50 (Jan): 1014–1024. https://doi.org/10.1016/j.aap.2012.08.018.
Jimenez, F., J. E. Naranjo, and F. Garcia. 2012. “An improved method to calculate the time-to-collision of two vehicles.” Int. J. Intell. Transp. Syst. Res. 11 (1): 34–42. https://doi.org/10.1007/s13177-012-0054-4.
Kim, J., Y. Wang, and G. F. Ulfarsson. 2007. “Modelling the probability of freeway rear-end crash occurrence.” J. Transp. Eng. 133 (1): 11–19. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:1(11).
Kuang, Y., X. Qu, and S. Wang. 2014. “Propagation and dissipation of crash risk on saturated freeways.” Transp. B: Transp. Dyn. 2 (3): 203–214. https://doi.org/10.1080/21680566.2014.930675.
Kuang, Y., X. Qu, and S. Wang. 2015. “A tree-structured crash surrogate measure for freeways.” Accid. Anal. Prev. 77 (Apr): 137–148. https://doi.org/10.1016/j.aap.2015.02.007.
Lee, J., B. Nam, and M. Abdel-Aty. 2008. “Effects of pavement surface conditions on traffic crash severity.” J. Transp. Eng. 141 (10): 04015020. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000785.
Li, Z., W. Wang, R. Chen, P. Liu, and C. Xu. 2013. “Evaluation of the impacts of speed variation on freeway traffic collisions in various traffic states.” Traffic Inj. Prev. 14 (8): 861–866. https://doi.org/10.1080/15389588.2013.775433.
Lord, D. 2002. “Issues related to the application of accident prediction models for the computation of accident risk on transportation networks.” Transp. Res. Rec. 1784 (1): 17–26. https://doi.org/10.3141/1784-03.
Lord, D., and B. N. Persaud. 2000. “Accident prediction models with and without trend: Application of the generalized estimating equations procedure.” Transp. Res. Rec. 1717 (1): 102–108. https://doi.org/10.3141/1717-13.
Lyu, P., Y. Lin, L. Wang, and X. Yang. 2017. “Variable speed limit control for delay and crash reductions at freeway work zone area.” J. Transp. Eng. Part A: Syst. 143 (12): 04017062. https://doi.org/10.1061/JTEPBS.0000099.
Meng, Q., and X. Qu. 2012. “Estimation of rear-end vehicle crash frequencies in urban road tunnels.” Accid. Anal. Prev. 48 (Sep): 254–263. https://doi.org/10.1016/j.aap.2012.01.025.
Meng, Q., and J. Weng. 2011. “Evaluation of rear-end crash risk at work zone using work zone traffic data.” Accid. Anal. Prev. 43 (4): 1291–1300. https://doi.org/10.1016/j.aap.2011.01.011.
Miaou, S. P. 1994. “The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions.” Accid. Anal. Prev. 26 (Jul): 471–482. https://doi.org/10.1016/0001-4575(94)90038-8.
Miaou, S. P., and H. Lum. 1993. “Modeling vehicle accidents and highway geometric design relationships.” Accid. Anal. Prev. 25 (6): 689–709. https://doi.org/10.1016/0001-4575(93)90034-T.
National Highway Traffic Safety Administration (NHTSA). 2015. “Addressing deadly rear-end crashes.” Accessed April 2, 2019. https://www.ntsb.gov/safety/safety-alerts/Documents/SA-046.pdf.
Oh, C., and T. Kim. 2010. “Estimation of rear-end crash potential using vehicle trajectory data.” Accid. Anal. Prev. 42 (6): 1888–1893. https://doi.org/10.1016/j.aap.2010.05.009.
Ozbay, K., H. Yang, B. Bartin, and S. Mudigonda. 2008. “Derivation and validation of new simulation-based surrogate safety measure.” Transp. Res. Rec. 2083 (1): 105–113. https://doi.org/10.3141/2083-12.
Papadimitriou, E., and A. Theofilatos. 2017. “Meta-analysis of crash-risk factors in freeway entrance and exit areas.” J. Transp. Eng. Part A: Systems 143 (10): 04017050. https://doi.org/10.1061/JTEPBS.0000082.
Pearl, J. 2000. Causality: Models, reasoning, and inference. Cambridge, UK: Cambridge University Press.
Qu, X., Y. Kuang, E. Oh, and S. Jin. 2014a. “Safety evaluation for expressways: A comparative study for macroscopic and microscopic indicators.” Traffic Inj. Prev. 15 (1): 89–93. https://doi.org/10.1080/15389588.2013.782400.
Qu, X., Y. Yang, Z. Liu, S. Jin, and J. Weng. 2014b. “Potential crash risks of expressway on-ramps and off-ramps: A case study in Beijing, China.” Saf. Sci. 70 (Dec): 58–62. https://doi.org/10.1016/j.ssci.2014.04.016.
Saccomanno, F. F., F. Cunto, G. Guido, and A. Vitale. 2008. “Comparing safety at signalized intersections and roundabouts using simulated rear-end conflicts.” Transp. Res. Rec. 2078 (1): 90–95. https://doi.org/10.3141/2078-12.
Son, H. T., Y.-J. Kweon, and B. T. Park. 2011. “Development of crash prediction models with individual vehicular data.” Transp. Res. Part C: Emerg. Technol. 19 (6): 1353–1363. https://doi.org/10.1016/j.trc.2011.03.002.
Tarko, A., G. Davis, N. Saunier, T. Sayed, S. Washington. 2009. “White paper: Surrogate measures of safety.” In Committee on Safety Data Evaluation and Analysis. Washington, DC: Transportation Research Board.
Triggs, T., and W. Harris, (1982). Reaction time of drivers to road stimuli. Clayton, Australia: Monash Univ.
USDOT. 2005. “Traffic safety fact 2005. NHTSA’s national centre for statistic and analysis (NCSA).” Accessed February 20, 2019. http://www-nrd.nhtsa.dot.gov/Pubs/810631.pdf.
Van der horst, R. 1991. “Time-to-collision as a cue for decision making in braking.” In Vision in vehicles III, 19–26. Amsterdam, Netherlands: Elsevier Science.
Vogel, K. 2003. “A comparison of headway and time to collision as safety indicators.” Accid. Anal. Prev. 35 (3): 427–433. https://doi.org/10.1016/S0001-4575(02)00022-2.
Wang, C., and N. Stamatiadis. 2013a. “A surrogate safety measure for simulation-based conflict study.” Transp. Res. Rec. 2386 (1): 72–80. https://doi.org/10.3141/2386-09.
Wang, C., and N. Stamatiadis. 2013b. “The derivation of a new surrogate measure of crash severity.” In Proc., 93rd Annual Meeting of the Transportation Research Board. Washington, DC: Transportation Research Board.
Wang, C., and N. Stamatiadis. 2014. “Evaluation of a simulation-based surrogate safety metric.” Accid. Anal. Prev. 71 (Oct): 82–92. https://doi.org/10.1016/j.aap.2014.05.004.
Weng, J., and Q. Meng. 2011. “Analysis of driver casualty risk for different work zone types.” Accid. Anal. Prev. 43 (5): 1811–1817. https://doi.org/10.1016/j.aap.2011.04.016.
World Health Organization (WHO). 2015. Global status report on road safety 2015: Supporting a decade of action. Geneva: World Health Organization.
Xie, K., D. Yang, K. Ozbay, and H. Yang. 2019. “Use of real-world connected vehicle data in identifying high-risk locations based on a new surrogate safety measure.” Accid. Anal. Prev. 125 (Apr): 311–319. https://doi.org/10.1016/j.aap.2018.07.002.
Xu, C., Y. Yang, S. Jin, Z. Qu, and L. Hou. 2016. “Potential risk and its influencing factors for separated bicycle paths.” Accid. Anal. Prev. 87 (Feb): 59–67. https://doi.org/10.1016/j.aap.2015.11.014.
You, Y., L. Sun, W. Gu, (2012). “Reliability-based risk analysis of roadway horizontal curves.” J. Transp. Eng. 138 (8): 1071–1081. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000402.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 8 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: May 22, 2019
Accepted: Mar 17, 2020
Published online: Jun 12, 2020
Published in print: Aug 1, 2020
Discussion open until: Nov 12, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.