Investigating factors affecting rural crash frequency at marginal areas around cities in Iran: a random parameter modeling approach

References

• Abdel-Aty, M., P. C. Devarasetty, and A. Pande. 2009. “Safety Evaluation of Multilane Arterials in Florida.” Accident Analysis & Prevention 41 (4): 777–788. doi:10.1016/j.aap.2009.03.015.
   PubMed Web of Science ®Google Scholar
• Abdel-Aty, M. A., and A. E. Radwan. 2000. “Modeling Traffic Accident Occurrence and Involvement.” Accident Analysis & Prevention 32 (5): 633–642. doi:10.1016/S0001-4575(99)00094-9.
   PubMed Web of Science ®Google Scholar
• Afandizadeh, S., and S. Hassanpour. 2020. “Evaluating the Effect of Roadway and Development Factors on the Rural Road Safety Risk Index.” Advances in Civil Engineering 2020: 1–14. doi:10.1155/2020/7820565.
   Web of Science ®Google Scholar
• Afghari, A. P., S. Washington, M. M. Haque, and Z. Li. 2018. “A Comprehensive Joint Econometric Model of Motor Vehicle Crashes Arising from Multiple Sources of Risk.” Analytic Methods in Accident Research 18: 1–14. doi:10.1016/j.amar.2018.03.002.
   Web of Science ®Google Scholar
• Ahmadinejad, M., S. Afandizadeh Zargari, and R. Jalalkamali . 2018. “Are Deceleration Numbers a Suitable Index for Road Safety?” Proceedings of the Institution of Civil Engineers-Transport . 171:5, 247-252. 10.1680/jtran.16.00117.
   Google Scholar
• Ahmed, M., H. Huang, M. Abdel-Aty, and B. Guevara. 2011. “Exploring a Bayesian Hierarchical Approach for Developing Safety Performance Functions for a Mountainous Freeway.” Accident Analysis & Prevention 43 (4): 1581–1589. doi:10.1016/j.aap.2011.03.021.
   PubMed Web of Science ®Google Scholar
• Alrejjal, A., M. Moomen, and K. Ksaibati. 2021. “Evaluating the Effectiveness of Law Enforcement in Reducing Truck Crashes for a Rural Mountainous Freeway in Wyoming.” Transportation Letters 1–11. doi:10.1080/19427867.2021.1949089.
   Web of Science ®Google Scholar
• Anastasopoulos, P. C., and F. L. Mannering. 2009. “A Note on Modeling Vehicle Accident Frequencies with random-parameters Count Models.” Accident Analysis & Prevention 41 (1): 153–159. doi:10.1016/j.aap.2008.10.005.
   PubMed Web of Science ®Google Scholar
• Anastasopoulos, P. C., and F. L. Mannering. 2016. “The Effect of Speed Limits on Drivers’ Choice of Speed: A Random Parameters Seemingly Unrelated Equations Approach.” Analytic Methods in Accident Research 10: 1–11. doi:10.1016/j.amar.2016.03.001.
   Web of Science ®Google Scholar
• Anastasopoulos, P. C., F. L. Mannering, V. N. Shankar, and J. E. Haddock. 2012. “A Study of Factors Affecting Highway Accident Rates Using the random-parameters Tobit Model.” Accident Analysis & Prevention 45: 628–633. doi:10.1016/j.aap.2011.09.015.
   PubMed Web of Science ®Google Scholar
• Ayati, E., and E. Abbasi. 2011. “Investigation on the Role of Traffic Volume in Accidents on Urban Highways.” Journal of Safety Research 42 (3): 209–214. doi:10.1016/j.jsr.2011.03.006.
   PubMed Web of Science ®Google Scholar
• Boroujerdian, A. M., M. Saffarzadeh, and V. Abolhasannejad. 2010. “Developing a Model for Prioritising High Crash Road Segments.” Proceedings of the Institution of Civil Engineers-Transport 163 (1): 19–29. doi:10.1680/tran.2010.163.1.19.
   Web of Science ®Google Scholar
• Buddhavarapu, P., A. Banerjee, and J. A. Prozzi. 2013. “Influence of Pavement Condition on Horizontal Curve Safety.” Accident Analysis & Prevention 52: 9–18. doi:10.1016/j.aap.2012.12.010.
   PubMed Web of Science ®Google Scholar
• Buddhavarapu, P., J. G. Scott, and J. A. Prozzi. 2016. “Modeling Unobserved Heterogeneity Using Finite Mixture Random Parameters for Spatially Correlated Discrete Count Data.” Transportation Research Part B: Methodological 91: 492–510. doi:10.1016/j.trb.2016.06.005.
   Web of Science ®Google Scholar
• Cafiso, S., C. D’Agostino, and B. Persaud. 2013. “Investigating Influence of Segmentation in Estimating Safety Performance Functions for Roadway Sections.” Accident; Analysis and Prevention 60: 324–333. No. 13-4372. doi:10.1016/j.aap.2013.06.010.
   PubMed Web of Science ®Google Scholar
• Cai, Q., M. Abdel-Aty, J. Lee, L. Wang, and X. Wang. 2018. “Developing a Grouped Random Parameters Multivariate Spatial Model to Explore Zonal Effects for Segment and Intersection Crash Modeling.” Analytic Methods in Accident Research 19: 1–15. doi:10.1016/j.amar.2018.05.001.
   Web of Science ®Google Scholar
• Caliendo, C., M. L. D. Guglielmo, and M. Guida. 2013. “A crash-prediction Model for Road Tunnels.” Accident Analysis & Prevention 55: 107–115. doi:10.1016/j.aap.2013.02.024.
   PubMed Web of Science ®Google Scholar
• Chen, E., and A. P. Tarko. 2014. “Modeling Safety of Highway Work Zones with Random Parameters and Random Effects Models.” Analytic Methods in Accident Research 1: 86–95. doi:10.1016/j.amar.2013.10.003.
   Google Scholar
• Chen, F., M. Xiaoxiang, C. Suren, and Y. Lin. 2016. “Crash Frequency Analysis Using Hurdle Models with Random Effects considering Short-Term Panel Data.” International Journal of Environmental Research and Public Health 13 (11): 1043. doi:10.3390/ijerph13111043.
   PubMed Web of Science ®Google Scholar
• Chin, H. C., and M. A. Quddus. 2003. “Applying the Random Effect Negative Binomial model to Examine Traffic Accident Occurrence at Signalized Intersections.” Accident Analysis & Prevention 35 (2): 253–259. doi:10.1016/S0001-4575(02)00003-9.
   PubMed Web of Science ®Google Scholar
• Coruh, E., A. Bilgic, and A. Tortum. 2015. “Accident Analysis with Aggregated Data: The Random Parameters Negative Binomial Panel Count Data Model.” Analytic Methods in Accident Research 7: 37–49. doi:10.1016/j.amar.2015.07.001.
   Web of Science ®Google Scholar
• Dinu, R. R., and A. Veeraragavan. 2011. “Random Parameter Models for Accident Prediction on two-lane Undivided Highways in India.” Journal of Safety Research 42 (1): 39–42. doi:10.1016/j.jsr.2010.11.007.
   PubMed Web of Science ®Google Scholar
• Dong, C., S. S. Nambisan, S. H. Richards, and Z. Ma. 2015. “Assessment of the Effects of Highway Geometric Design Features on the Frequency of Truck Involved Crashes Using Bivariate Regression.” Transportation Research Part A: Policy and Practice 75: 30–41. doi:10.1016/j.tra.2015.03.007.
   Web of Science ®Google Scholar
• Donnell, E. T., and J. M. Mason Jr. 2006. “Predicting the Frequency of Median Barrier Crashes on Pennsylvania Interstate Highways.” Accident Analysis & Prevention 38 (3): 590–599. doi:10.1016/j.aap.2005.12.011.
   PubMed Web of Science ®Google Scholar
• Effati, M., M. A. Rajabi, F. Samadzadegan, and J. A. R. Blais. 2012. “Developing a Novel Method for Road Hazardous Segment Identification Based on Fuzzy Reasoning and GIS.” Journal of Transportation Technologies 2 (1): 32–40. doi:10.4236/jtts.2012.21004.
   Google Scholar
• Effati, M., M. A. Rajabi, F. Samadzadegan, and S. Shabani. 2014. “A Geospatial neuro-fuzzy Approach for Identification of Hazardous Zones in Regional Transportation Corridors.” International Journal of Civil Engineering 12 (3): 289–303. http://ijce.iust.ac.ir/article-1-825-en.html
   Web of Science ®Google Scholar
• Ehsani Sohi, M., H. Dashtestaninejad, and E. Khademi. 2019. “Effects of Roadway and Traffic Characteristics on Accidents Frequency at City Entrance Zone.” International Journal of Transportation Engineering 7 (2): 139–152. 10.22119/IJTE.2018.130189.1404
   Google Scholar
• Eluru, N., and C. R. Bhat. 2007. “A Joint Econometric Analysis of Seat Belt Use and crash-related Injury Severity.” Accident Analysis & Prevention 39 (5): 1037–1049. doi:10.1016/j.aap.2007.02.001.
   PubMed Web of Science ®Google Scholar
• Elyasi, M. R., M. Saffarzadeh, and A. M. Boroujerdian. 2016. “A Novel Dynamic Segmentation Model for Identification and Prioritization of Black Spots Based on the Pattern of Potential for Safety Improvement.” Transportation Research Part A 91: 346–357. doi:10.1016/j.tra.2016.06.020.
   Google Scholar
• Elyasi, M. R., M. Saffarzadeh, and A. M. Boroujerdian. 2018. “Assessing the Interrelations of Traffic Collisions’ Risk Factors.” Proceedings of the Institution of Civil Engineers-Transport 171 (6): 309–318. doi:10.1680/jtran.16.00070.
   Web of Science ®Google Scholar
• Faezi, S. F., and M. R. Elyasi (2020). “Predict Road Accidents Resulted from Carelessness Using Negative Binomial Regression Model (A Case Study of Rural Highways in Hamadan Province).” Journal of Transportation Research. http://www.trijournal.ir/article_119190.html?lang=en
   Google Scholar
• Fu, R., Y. Guo, W. Yuan, H. Feng, and Y. Ma. 2011. “The Correlation between Gradients of Descending Roads and Accident Rates.” Safety Science 49 (3): 416–423. doi:10.1016/j.ssci.2010.10.006.
   Web of Science ®Google Scholar
• Garach, L., J. de Oña, G. López, and L. Baena. 2016. “Development of Safety Performance Functions for Spanish two-lane Rural Highways on Flat Terrain.” Accident Analysis & Prevention 95: 250–265. doi:10.1016/j.aap.2016.07.021.
   PubMed Web of Science ®Google Scholar
• Gong, H., F. Wang, B. B. Zhou, and S. Dent. 2020. “Application of Random Effects Negative Binomial Model with Clustered Dataset for Vehicle Crash Frequency Analysis.” International Journal of Transportation Science and Technology 9 (3): 183–194. doi:10.1016/j.ijtst.2020.03.010.
   Google Scholar
• Greene, W. H. 2012. Econometric Analysis, Seventh. Boston, MA: Prentice Hall.
   Google Scholar
• Guo, Y., A. Osama, and T. Sayed. 2018. “A cross-comparison of Different Techniques for Modeling macro-level Cyclist Crashes.” Accident Analysis & Prevention 113: 38–46. doi:10.1016/j.aap.2018.01.015.
   PubMed Web of Science ®Google Scholar
• Han, C., H. Huang, J. Lee, and J. Wang. 2018. “Investigating Varying Effect of road-level Factors on Crash Frequency across Regions: A Bayesian Hierarchical Random Parameter Modeling Approach.” Analytic Methods in Accident Research 20: 81–91. doi:10.1016/j.amar.2018.10.002.
   Web of Science ®Google Scholar
• Hauer, E. 2015. The Art of Regression Modelling in Road Safety. New York: Springer press. doi:10.1007/978-3-319-12529-9.
   Google Scholar
• Hosseinlou, M. H., A. Mahdavi, and M. J. Nooghabi. 2018. “Validation of the Influencing Factors Associated with Traffic Violations and Crashes on Freeways of Developing Countries: A Case Study of Iran.” Accident Analysis & Prevention 121: 358–366. doi:10.1016/j.aap.2018.06.009.
   PubMed Web of Science ®Google Scholar
• Hosseinlou, M. H., and M. Sohrabi. 2009. “Predicting and Identifying Traffic Hot Spots Applying neuro-fuzzy Systems in Intercity Roads.” International Journal of Environmental Science & Technology 6 (2): 309–314. doi:10.1007/BF03327634.
   Web of Science ®Google Scholar
• Hosseinpour, M., A. S. Yahaya, and A. F. Sadullah. 2014. “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: 209–222. doi:10.1016/j.aap.2013.10.001.
   PubMed Web of Science ®Google Scholar
• Hou, Q., A. P. Tarko, and X. Meng. 2018. “Investigating Factors of Crash Frequency with Random Effects and Random Parameters Models: New Insights from Chinese Freeway Study.” Accident Analysis & Prevention 120: 1–12. doi:10.1016/j.aap.2018.07.010.
   PubMed Web of Science ®Google Scholar
• Huang, H., F. Chang, H. Zhou, and J. Lee. 2019. “Modeling Unobserved Heterogeneity for Zonal Crash Frequencies: A Bayesian Multivariate random-parameters Model with Mixture Components for Spatially Correlated Data.” Analytic Methods in Accident Research 24: 100105. doi:10.1016/j.amar.2019.100105.
   Web of Science ®Google Scholar
• Huo, X., J. Leng, Q. Hou, L. Zheng, and L. Zhao. 2020. “Assessing the Explanatory and Predictive Performance of a Random Parameters Count Model with Heterogeneity in Means and Variances.” Accident Analysis & Prevention 147: 105759. doi:10.1016/j.aap.2020.105759.
   PubMed Web of Science ®Google Scholar
• Imaninasab, R., E. Sekhavati, and M. Hajihoseinloo. 2016. “Modeling Crash Frequency of Heavy Vehicles in Rural Freeways.” Journal of Traffic and Logistics Engineering 4 (2). doi:10.18178/jtle.4.2.98-102.
   Google Scholar
• Iran Road Maintenance and Transportation Organization (RMTO). 2020. “Road Statistical Yearbook.” http://www.rmto.ir/Pages/Home.aspx
   Google Scholar
• Jung, S., K. Jang, Y. Yoon, and S. Kang. 2014. “Contributing Factors to Vehicle to Vehicle Crash Frequency and Severity under Rainfall.” Journal of Safety Research 50: 1–10. doi:10.1016/j.jsr.2014.01.001.
   PubMed Web of Science ®Google Scholar
• Kabli, A., T. Bhowmik, and N. Eluru. 2020. “A Multivariate Approach for Modeling Driver Injury Severity by Body Region.” Analytic Methods in Accident Research 28: 100129. doi:10.1016/j.amar.2020.100129.
   Web of Science ®Google Scholar
• Khoda Bakhshi, A., and M. M. Ahmed. 2021. “Coping with Endogeneity and Unobserved Heterogeneity in real-time Clustering Critical Crash Occurrences Nested within Weather and Road Surface Conditions.” International Journal of Injury Control and Safety Promotion 28 (2): 208–221. doi:10.1080/17457300.2021.1907595.
   PubMed Web of Science ®Google Scholar
• Khoda Bakhshi, A., and M. M. Ahmed. 2021a. “Practical Advantage of Crossed Random Intercepts under Bayesian Hierarchical Modeling to Tackle Unobserved Heterogeneity in Clustering Critical versus non-critical Crashes.” Accident Analysis & Prevention 149: 105855. doi:10.1016/j.aap.2020.105855.
   PubMed Web of Science ®Google Scholar
• Kim, K., I. M. Brunner, and E. Y. Yamashita. 2006. “Influence of Land Use, Population, Employment, and Economic Activity on Accidents.” Transportation Research Record: Journal of the Transportation Research Board 1953 (1): 56–64. doi:10.1177/0361198106195300107.
   Google Scholar
• La Torre, F., M. Meocci, L. Domenichini, V. Branzi, and A. Paliotto. 2019. “Development of an Accident Prediction Model for Italian Freeways.” Accident Analysis & Prevention 124: 1–11. doi:10.1016/j.aap.2018.12.023.
   PubMed Web of Science ®Google Scholar
• Lord, D., and F. Mannering. 2010. “The Statistical Analysis of crash-frequency Data: A Review and Assessment of Methodological Alternatives.” Transportation Research Part A: Policy and Practice 44 (5): 291–305. doi:10.1016/j.tra.2010.02.001.
   Web of Science ®Google Scholar
• Lord, D., S. P. Washington, and J. N. Ivan. 2005. “Poisson, Poisson-gamma and Zero Inflated Regression Models of Motor Vehicle Crashes: Balancing Statistical Fit and Theory.” Accident Analysis and Prevention 37 (1): 35–46. 10.1016/j.aap.2004.02.004
   PubMed Web of Science ®Google Scholar
• Lord, D., S. P. Washington, and J. N. Ivan. 2007. “Further Notes on the Application of Zero Inflated Models in Highway Safety.” Accident Analysis and Prevention 39 (1): 53–57. 10.1016/j.aap.2006.06.004
   PubMed Web of Science ®Google Scholar
• Mahmud, S. S., L. Ferreira, M. S. Hoque, and A. Tavassoli. 2019. “Micro-level Safety Risk Assessment Model for A two-lane Heterogeneous Traffic Environment in A Developing Country: A Comparative Crash Probability Modeling Approach.” Journal of Safety Research 69: 125–134. doi:10.1016/j.jsr.2019.03.008.
   PubMed Web of Science ®Google Scholar
• Malyshkina, N. V., and F. L. Mannering. 2010. “Zero-state Markov Switching count-data Models: An Empirical Assessment.” Accident Analysis & Prevention 42 (1): 122–130. doi:10.1016/j.aap.2009.07.012.
   PubMed Web of Science ®Google Scholar
• Malyshkina, N. V., F. L. Mannering, and A. P. Tarko. 2009. “Markov Switching Negative Binomial Models: An Application to Vehicle Accident Frequencies.” Accident Analysis & Prevention 41 (2): 217–226. doi:10.1016/j.aap.2008.11.001.
   PubMed Web of Science ®Google Scholar
• Mannering, F. L., and C. R. Bhat. 2014. “Analytic Methods in Accident Research: Methodological Frontier and Future Directions.” Analytic Methods in Accident Research 1: 1–22. doi:10.1016/j.amar.2013.09.001.
   Google Scholar
• Mannering, F., C. R. Bhat, V. Shankar, and M. Abdel-Aty. 2020. “Big Data, Traditional Data and the Tradeoffs between Prediction and Causality in highway-safety Analysis.” Analytic Methods in Accident Research 25: 100113. doi:10.1016/j.amar.2020.100113.
   Web of Science ®Google Scholar
• Mannering, F. L., V. Shankar, and C. R. Bhat. 2016. “Unobserved Heterogeneity and the Statistical Analysis of Highway Accident Data.” Analytic Methods in Accident Research 11: 1–16. doi:10.1016/j.amar.2016.04.001.
   Web of Science ®Google Scholar
• Ma, Z., H. Zhang, I. Steven, J. Chien, J. Wang, and C. Dong. 2017. “Predicting Expressway Crash Frequency Using A Random Effect Negative Binomial Model: A Case Study in China.” Accident Analysis & Prevention 98: 214–222. doi:10.1016/j.aap.2016.10.012.
   PubMed Web of Science ®Google Scholar
• Milton, J., V. Shankar, and F. Mannering. 2008. “Highway Accident Severities and the Mixed Logit Model: An Exploratory Empirical Analysis.” Accident Analysis and Prevention 40 (1): 260–266. doi:10.1016/j.aap.2007.06.006.
   PubMed Web of Science ®Google Scholar
• Mohammadnazar, A., R. Arvin, and A. J. Khattak. 2021. “Classifying Travelers’ Driving Style Using Basic Safety Messages Generated by Connected Vehicles: Application of Unsupervised Machine Learning.” Transportation Research Part C: Emerging Technologies 122: 102917. doi:10.1016/j.trc.2020.102917.
   Web of Science ®Google Scholar
• Mohammadnazar, A., I. Mahdinia, N. Ahmad, A. J. Khattak, and J. Liu. 2021a. “Understanding How Relationships between Crash Frequency and Correlates Vary for Multilane Rural Highways: Estimating Geographically and Temporally Weighted Regression Models.” Accident Analysis & Prevention 157: 106146. doi:10.1016/j.aap.2021.106146.
   PubMed Web of Science ®Google Scholar
• Mohaymany, A. S., M. Shahri, and B. Mirbagheri. 2013. “GIS-based Method for Detecting high-crash-risk Road Segments Using Network Kernel Density Estimation.” Geo-spatial Information Science 16 (2): 113–119. doi:10.1080/10095020.2013.766396.
   Google Scholar
• Moomen, M., M. Rezapour, M. Raja, and K. Ksaibati. 2020. “Predicting Downgrade Crash Frequency with the random-parameters Negative Binomial Model: Insights into the Impacts of Geometric Variables on Downgrade Crashes in Wyoming.” IATSS Research 44 (2): 94–102. doi:10.1016/j.iatssr.2019.09.002.
   Web of Science ®Google Scholar
• Mousavi, S. M., H. Marzoughi, S. A. Parr, B. Wolshon, and A. Pande (2019). “A Mixed Crash Frequency Estimation Model for Interrupted Flow Segments.” International Conference on Transportation and Development 2019: Smarter and Safer Mobility and Cities (pp. 72–83). Reston, VA: American Society of Civil Engineers. 10.1061/9780784482575.008
   Google Scholar
• Naik, B., L. W. Tung, S. Zhao, and A. J. Khattak. 2016. “Weather Impacts on single-vehicle Truck Crash Injury Severity.” Journal of Safety Research 58: 57–65. doi:10.1016/j.jsr.2016.06.005.
   PubMed Web of Science ®Google Scholar
• Nassiri, H., P. Najafi, and A. Mohamadian Amiri. 2014. “Prediction of Roadway Accident Frequencies: Count Regressions versus Machine Learning Models.” Scientia Iranica 21 (2): 263–275. http://scientiairanica.sharif.edu/article_1630.html
   Web of Science ®Google Scholar
• Naznin, F., G. Currie, D. Logan, and M. Sarvi. 2016. “Application of a Random Effects Negative Binomial Model to Examine tram-involved Crash Frequency on Route Sections in Melbourne, Australia.” Accident Analysis & Prevention 92: 15–21. doi:10.1016/j.aap.2016.03.012.
   PubMed Web of Science ®Google Scholar
• Park, J., M. Abdel-Aty, and J. H. Wang. 2017. “Time Series Trends of the Safety Effects of Pavement Resurfacing.” Accident Analysis & Prevention 101: 78–86. doi:10.1016/j.aap.2017.02.006.
   PubMed Web of Science ®Google Scholar
• Rusli, R., M. M. Haque, M. King, and W. S. Voon. 2017. “Single-vehicle Crashes along Rural Mountainous Highways in Malaysia: An Application of Random Parameters Negative Binomial Model.” Accident Analysis & Prevention 102: 153–164. doi:10.1016/j.aap.2017.03.002.
   PubMed Web of Science ®Google Scholar
• Russo, B. J., P. T. Savolainen, W. H. Schneider IV, and P. C. Anastasopoulos. 2014. “Comparison of Factors Affecting Injury Severity in Angle Collisions by Fault Status Using a Random Parameters Bivariate Ordered Probit Model.” Analytic Methods in Accident Research 2: 21–29. doi:10.1016/j.amar.2014.03.001.
   Google Scholar
• Sadeghi, A., E. Ayati, and M. P. Neghab. 2013. “Identification and Prioritization of Hazardous Road Locations by Segmentation and Data Envelopment Analysis Approach.” PROMET-Traffic&Transportation 25 (2): 127–136. doi:10.7307/ptt.v25i2.1295.
   Web of Science ®Google Scholar
• Saeed, T. U., T. Hall, H. Baroud, and M. J. Volovski. 2019. “Analyzing Road Crash Frequencies with Uncorrelated and Correlated random-parameters Count Models: An Empirical Assessment of Multilane Highways.” Analytic Methods in Accident Research 23: 100101. doi:10.1016/j.amar.2019.100101.
   Web of Science ®Google Scholar
• Sajed, Y., G. Shafabakhsh, and M. Bagheri. 2019. “Hotspot Location Identification Using Accident Data, Traffic and Geometric Characteristics.” Engineering Journal 23 (6): 191–207. doi:10.4186/ej.2019.23.6.191.
   Google Scholar
• Shafabakhsh, G. A., A. Famili, and M. Akbari. 2016. “Spatial Analysis of Data Frequency and Severity of Rural Accidents.” Transportation Letters 1–8. doi:10.1080/19427867.2016.1138605.
   PubMedGoogle Scholar
• Shamanian Esfahani, H., S. Afandizadeh, and A. Naderan. 2022. “Investigating the Effect of Marginal Areas around the Cities on Rural Road Accidents in Iran Using Linear and Logistic Regression Approaches.” International Journal of Transportation Engineering 9 (3): 693–711. doi:10.22119/ijte.2021.284119.1567.
   Google Scholar
• Shankar, V. N., R. B. Albin, J. C. Milton, and F. L. Mannering. 1998. “Evaluation Median crossover Likelihoods with Clustered Accident Counts: An Empirical Inquiry using the Random Effect Negative Binomial Model.” Transportation Research Record: Journal of the Transportation Research Board 1635 (1): 44–48. doi:10.3141/1635-06.
   Google Scholar
• Shankar, V., F. Mannering, and W. Barfield. 1995. “Effect of Roadway Geometrics and Environmental Factors on Rural Freeway Accident Frequencies.” Accident Analysis & Prevention 27 (3): 371–389. doi:10.1016/0001-4575(94)00078-Z.
   PubMed Web of Science ®Google Scholar
• Shaon, M. R. R., X. Qin, M. Shirazi, D. Lord, and S. R. Geedipally. 2018. “Developing a Random Parameters Negative Binomial-Lindley Model to Analyze Highly over-dispersed Crash Count Data.” Analytic Methods in Accident Research 18: 33–44. doi:10.1016/j.amar.2018.04.002.
   Web of Science ®Google Scholar
• Singh, G., M. Pal, Y. Yadav, and T. Singla. 2020. “Deep Neural network-based Predictive Modeling of Road Accidents.” Neural Computing & Applications 1–10. doi:10.1007/s00521-019-04695-8.
   Google Scholar
• Tafti, M. F., and R. Roshani. 2021. “Development of Models to Study Traffic Accidents on the Final Sections of Access Roads to the Cities: A Case Study of Three Major Iranian Cities.” cities 59 (3): 129–148. 10.5604/01.3001.0015.2646
   Google Scholar
• Washington, S., M. Karlaftis, F. Mannering, and P. Anastasopoulos. 2020. Statistical and Econometric Methods for Transportation Data Analysis. New York: Chapman and Hall/CRC. doi:10.1201/9780429244018.
   Google Scholar
• Wen, X., Y. Xie, L. Wu, and L. Jiang. 2021. “Quantifying and Comparing the Effects of Key Risk Factors on Various Types of Roadway Segment Crashes with LightGBM and SHAP.” Accident Analysis & Prevention 159: 106261. doi:10.1016/j.aap.2021.106261.
   PubMed Web of Science ®Google Scholar
• World Health Organization (WHO). 2018. “Global Status Report on Road Safety.” https://www.who.int/publications/i/item/global-status-report-on-road-safety-2018
   Google Scholar
• Wu, P., L. Song, and X. Meng. 2021. “Influence of Built Environment and Roadway Characteristics on the Frequency of Vehicle Crashes Caused by Driver Inattention: A Comparison between Rural Roads and Urban Roads.” Journal of Safety Research 79: 199–210. doi:10.1016/j.jsr.2021.09.001.
   PubMed Web of Science ®Google Scholar
• Xiong, Y., and F. L. Mannering. 2013. “The Heterogeneous Effects of Guardian Supervision on Adolescent driver-injury Severities: A finite-mixture random-parameters Approach.” Transportation Research Part B: Methodological 49: 39–54. doi:10.1016/j.trb.2013.01.002.
   Web of Science ®Google Scholar
• Xiong, Y., J. L. Tobias, and F. L. Mannering. 2014. “The Analysis of Vehicle Crash injury-severity Data: A Markov Switching Approach with road-segment Heterogeneity.” Transportation Research Part B: Methodological 67: 109–128. doi:10.1016/j.trb.2014.04.007.
   Web of Science ®Google Scholar
• Yaacob, W. F. W., M. A. Lazim, and Y. B. Wah (2010). “Evaluating Spatial and Temporal Effects of Accidents Likelihood Using Random Effects Panel Count Model.” 2010 International Conference on Science and Social Research (CSSR 2010) Kuala Lumpur, Malaysia (pp. 960–964). IEEE. 10.1109/CSSR.2010.5773927.
   Google Scholar
• Yan, Y., Y. Zhang, X. Yang, J. Hu, J. Tang, and Z. Guo. 2020. “Crash Prediction Based on Random Effect Negative Binomial Model considering Data Heterogeneity.” Physica A: Statistical Mechanics and Its Applications 547: 123858. doi:10.1016/j.physa.2019.123858.
   Web of Science ®Google Scholar
• Yu, R., M. Abdel-Aty, and M. Ahmed. 2013. “Bayesian Random Effect Models Incorporating real-time Weather and Traffic Data to Investigate Mountainous Freeway Hazardous Factors.” Accident Analysis & Prevention 50: 371–376. doi:10.1016/j.aap.2012.05.011.
   PubMed Web of Science ®Google Scholar
• Yu, R., Y. Wang, M. Quddus, and J. Li. 2019. “A Marginalized Random Effects Hurdle Negative Binomial Model for Analyzing refined-scale Crash Frequency Data.” Analytic Methods in Accident Research 22: 100092. doi:10.1016/j.amar.2019.100092.
   Web of Science ®Google Scholar
• Yu, R., Y. Xiong, and M. Abdel-Aty. 2015. “A Correlated Random Parameter Approach to Investigate the Effects of Weather Conditions on Crash Risk for A Mountainous Freeway.” Transportation Research Part C: Emerging Technologies 50: 68–77. doi:10.1016/j.trc.2014.09.016.
   Web of Science ®Google Scholar
• Zou, Y., and A. P. Tarko. 2016. “An Insight into the Performance of Road Barriers− Redistribution of barrier-relevant Crashes.” Accident Analysis & Prevention 96: 152–161. doi:10.1016/j.aap.2016.07.022.
   PubMed Web of Science ®Google Scholar
• Zou, Y., Y. Zhang, and D. Lord. 2013. “Application of Finite Mixture of Negative Binomial Regression Models with Varying Weight Parameters for Vehicle Crash Data Analysis.” Accident Analysis & Prevention 50: 1042–1051. doi:10.1016/j.aap.2012.08.004.
   PubMed Web of Science ®Google Scholar
• Zou, Y., Y. Zhang, and D. Lord. 2014. “Analyzing Different Functional Forms of the Varying Weight Parameter for Finite Mixture of Negative Binomial Regression Models.” Analytic Methods in Accident Research 1: 39–52. doi:10.1016/j.amar.2013.11.001.
   Google Scholar