Safety analysis of unsignalized intersections: a bivariate extreme value approach

References

• Allen, B. L., B. T. Shin, and P. Cooper. 1978. “Analysis of Traffic Conflicts and Collisions.” Transportation Research Record667: 67–74.
   Google Scholar
• Behbahani, H., N. Nadimi, and S. S. Naseralavi. 2015. “New Time-based Surrogate Safety Measure to Assess Crash Risk in Car-following Scenarios.” Transportation Letters 7: 229–238. doi:10.1179/1942787514Y.0000000051.
   Web of Science ®Google Scholar
• Beirlant, J., Y. Goegebeur, J. Teugels, J. Segers, D. De Waal, and C. Ferro. 2004. Statistics of Extremes: Theory and Applications, Statistics of Extremes: Theory and Applications. doi:10.1002/0470012382.
   Google Scholar
• Cavadas, J., C. L. Azevedo, H. Farah, and A. Ferreira. 2020. “Road Safety of Passing Maneuvers: A Bivariate Extreme Value Theory Approach under Non-stationary Conditions.” Accident Analysis and Prevention 134: 105315. doi:10.1016/j.aap.2019.105315.
   PubMed Web of Science ®Google Scholar
• Coles, S. G. 2001. An Introduction to Statistical Modeling of Extreme Values. London: Springer Series in Statistics. doi:10.1007/978-1-4471-3675-0.
   Google Scholar
• Coles, S. G., and J. A. Tawn. 1994. “Statistical Methods for Multivariate Extremes: An Application to Structural Design.” Applied Statistics 43: 1–48. doi:10.2307/2986112.
   Web of Science ®Google Scholar
• Das, S., and A. K. Maurya. 2020. “Bivariate Modeling of Time Headways in Mixed Traffic Streams: A Copula Approach.” Transportation Letters 12: 138–148. doi:10.1080/19427867.2018.1537209.
   Web of Science ®Google Scholar
• Eltrass, A., and M. Khalil. 2018. “Automotive Radar System for Multiple-vehicle Detection and Tracking in Urban Environments.” IET Intelligent Transport Systems 12: 783–792. doi:10.1049/iet-its.2017.0370.
   Web of Science ®Google Scholar
• ETSC. 2016. Reducing Casualties Involving Young Drivers and Riders in Europe. Bruxelles: European Transport Safety Council.
   Google Scholar
• Gecchele, G., F. Orsini, M. Gastaldi, and R. Rossi. 2019. “Freeway Rear-end Collision Risk Estimation with Extreme Value Theory Approach. A Case Study.” Transportation Research Procedia 37: 195–202. doi:10.1016/j.trpro.2018.12.183.
   Google Scholar
• Gettman, D., and L. Head. 2003. “Surrogate Safety Measures from Traffic Simulation Models.” Transportation Research Record 1840: 104–115. doi:10.3141/1840-12.
   Google Scholar
• Guo, Y., L. Zheng, and T. Sayed. 2020. “A Comparison of Collision-based and Conflict-based Safety Evaluation of Left-turn Bay Extension.” Transportmetrica A: Transport Science 16: 676–694. doi:10.1080/23249935.2020.1722286.
   Web of Science ®Google Scholar
• Ha, D.-H., M. Aron, and S. Cohen. 2012. “Time Headway Variable and Probabilistic Modeling.” Transportation Research Part C: Emerging Technologies 25: 181–201. doi:10.1016/j.trc.2012.06.002.
   Web of Science ®Google Scholar
• Hayward, J. C. 1972. “Near-miss Determination through Use of a Scale of Danger.” Highway Research Record. doi:TTSC7115.
   Google Scholar
• Johnsson, C., A. Laureshyn, and T. De Ceunynck. 2018. “In Search of Surrogate Safety Indicators for Vulnerable Road Users: A Review of Surrogate Safety Indicators.” Transport Reviews 38: 1–21. doi:10.1080/01441647.2018.1442888.
   Web of Science ®Google Scholar
• Jonasson, J. K., and H. Rootzén. 2014. “Internal Validation of Near-crashes in Naturalistic Driving Studies: A Continuous and Multivariate Approach.” Accident Analysis and Prevention 62: 102–109. doi:10.1016/j.aap.2013.09.013.
   PubMed Web of Science ®Google Scholar
• Laureshyn, A., Å. Svensson, and C. Hydén. 2010. “Evaluation of Traffic Safety, Based on Micro-level Behavioural Data: Theoretical Framework and First Implementation.” Accident Analysis and Prevention 42: 1637–1646. doi:10.1016/j.aap.2010.03.021.
   PubMed Web of Science ®Google Scholar
• Nadimi, N., D. R. Ragland, and A. Mohammadian Amiri. 2020. “An Evaluation of Time-to-collision as a Surrogate Safety Measure and a Proposal of a New Method for Its Application in Safety Analysis.” Transportation Letters 12: 491–500. doi:10.1080/19427867.2019.1650430.
   Web of Science ®Google Scholar
• Orsini, F., G. Gecchele, M. Gastaldi, and R. Rossi. 2019. “Collision Prediction in Roundabouts: A Comparative Study of Extreme Value Theory Approaches.” Transportmetrica A: Transport Science 15: 556–572. doi:10.1080/23249935.2018.1515271.
   Web of Science ®Google Scholar
• Orsini, F., G. Gecchele, M. Gastaldi, and R. Rossi. 2020a. “Large-scale Road Safety Evaluation Using Extreme Value Theory.” IET Intelligent Transport Systems 14: 1004–1012. doi:10.1049/iet-its.2019.0633.
   Web of Science ®Google Scholar
• Orsini, F., G. Gecchele, M. Gastaldi, and R. Rossi. 2020b. “Transferability and Seasonality in Extreme Value Theory Applications to Road Safety: A Case Study in an Italian Motorway.” Advances in Transportation Studies 2: 33–46.
   Google Scholar
• Persaud, B., T. Saleem, M. E. Granados, and T. Rajeswaran. 2018. “Can Crash Modification Factors Be Estimated from Surrogate Measures of Safety? Adv.” Advances in Transportation Studies 1: 149–162.
   Google Scholar
• Rossi, R., M. Gastaldi, and C. Meneguzzer. 2018. “Headway Distribution Effect on Gap-acceptance Behavior at Roundabouts: Driving Simulator Experiments in a Case Study.” Advances in Transportation Studies 46: 97–110. doi:10.4399/9788255186418.
   Google Scholar
• Rossi, R., C. Meneguzzer, F. Orsini, and M. Gastaldi. 2020. “Gap-acceptance Behavior at Roundabouts: Validation of a Driving Simulator Environment Using Field Observations.” Transportation Research Procedia 47: 27–34. doi:10.1016/j.trpro.2020.03.069.
   Google Scholar
• Sadeq, H., and T. Sayed. 2016. “Automated Roundabout Safety Analysis: Diagnosis and Remedy of Safety Problems.” Journal of Transportation Engineering 142: 04016062. Content ID 04016062. doi:10.1061/(ASCE)TE.1943-5436.0000887.
   Google Scholar
• Saha, P., R. Roy, A. K. Sarkar, and M. Pal. 2019. “Preferred Time Headway of Drivers on Two-lane Highways with Heterogeneous Traffic.” Transportation Letters 11: 200–207. doi:10.1080/19427867.2017.1312859.
   Web of Science ®Google Scholar
• Shekhar Babu, S., and P. Vedagiri. 2018. “Proactive Safety Evaluation of a Multilane Unsignalized Intersection Using Surrogate Measures.” Transportation Letters 10: 104–112. doi:10.1080/19427867.2016.1230172.
   Web of Science ®Google Scholar
• Shen, C., X. Zhao, Z. Liu, T. Gao, and J. Xu. 2020. “Joint Vehicle Detection and Distance Prediction via Monocular Depth Estimation.” IET Intelligent Transport Systems 14: 753–763. doi:10.1049/iet-its.2019.0376.
   Web of Science ®Google Scholar
• Songchitruksa, P., and A. P. Tarko. 2006. “The Extreme Value Theory Approach to Safety Estimation.” Accident Analysis and Prevention 38: 811–822. doi:10.1016/j.aap.2006.02.003.
   PubMed Web of Science ®Google Scholar
• Srinivasula, S. R., A. Chepuri, S. S. Arkatkar, and G. Joshi. 2020. “Developing Proximal Safety Indicators for Assessment of Un-signalized Intersection–a Case Study in Surat City.” Transportation Letters 12: 303–315. doi:10.1080/19427867.2019.1589162.
   Web of Science ®Google Scholar
• Tarko, A. P. 2018a. “Chapter 17. Surrogate Measures of Safety.” In Safe Mobility: Challenges, Methodology and Solutions, 383–405. doi:10.1108/S2044-994120180000011019.
   Google Scholar
• Tarko, A. P. 2018b. “Estimating the Expected Number of Crashes with Traffic Conflicts and the Lomax Distribution – A Theoretical and Numerical Exploration.” Accident Analysis and Prevention 113: 63–73. doi:10.1016/j.aap.2018.01.008.
   PubMed Web of Science ®Google Scholar
• Tolle, J. E. 1971. “The Lognormal Headway Distribution Model.” Traffic Engineering and Control 13: 22–24.
   Google Scholar
• Van Der Horst, R. 1990. A Time-based Analysis of Road User Behaviour in Normal and Critical Encounters. Technische Universiteit Delft. doi:uuid:8fb40be7-fae1-4481-bc37-12a7411b85c7.
   Google Scholar
• Wang, C., C. Xu, and Y. Dai. 2019. “A Crash Prediction Method Based on Bivariate Extreme Value Theory and Video-based Vehicle Trajectory Data.” Accident Analysis and Prevention 123: 365–373. doi:10.1016/j.aap.2018.12.013.
   PubMed Web of Science ®Google Scholar
• Zheng, L., K. Ismail, and X. Meng. 2014a. “Shifted Gamma-Generalized Pareto Distribution Model to Map the Safety Continuum and Estimate Crashes.” Safety Science 64: 155–162. doi:10.1016/j.ssci.2013.12.003.
   Web of Science ®Google Scholar
• Zheng, L., K. Ismail, and X. Meng. 2014b. “Freeway Safety Estimation Using Extreme Value Theory Approaches: A Comparative Study.” Accident Analysis and Prevention 62: 32–41. doi:10.1016/j.aap.2013.09.006.
   PubMed Web of Science ®Google Scholar
• Zheng, L., K. Ismail, T. Sayed, and T. Fatema. 2018a. “Bivariate Extreme Value Modeling for Road Safety Estimation.” Accident Analysis and Prevention 120: 83–91. doi:10.1016/j.aap.2018.08.004.
   PubMed Web of Science ®Google Scholar
• Zheng, L., and T. Sayed. 2019. “Application of Extreme Value Theory for Before-After Road Safety Analysis.” Transportation Research Record 0361198119841555. doi:10.1177/0361198119841555.
   Web of Science ®Google Scholar
• Zheng, L., T. Sayed, and M. Essa. 2019. “Validating the Bivariate Extreme Value Modeling Approach for Road Safety Estimation with Different Traffic Conflict Indicators.” Accident Analysis and Prevention 123: 314–323. doi:10.1016/j.aap.2018.12.007.
   PubMed Web of Science ®Google Scholar
• Zheng, L., T. Sayed, and A. Tageldin. 2018b. “Before-after Safety Analysis Using Extreme Value Theory: A Case of Left-turn Bay Extension.” Accident Analysis and Prevention 121: 258–267. doi:10.1016/j.aap.2018.09.023.
   PubMed Web of Science ®Google Scholar