Journal Publications
* Underlined names show advised/co-advised students.
1. Gil-Marin, J.K., Shirazi., M. & Ivan, J. (2024). Assessing the Negative Binomial-Lindley Model for Crash Hotspot Identification: Insights from Monte Carlo Simulation Analysis. Accident Analysis & Prevention (accepted for publication.)
2. Vergara, E., Aviles-Ordonez, J., Xie, Y., & Shirazi, M. (2024). Understanding Speeding Behavior on Interstate Horizontal Curves and Ramps Using Networkwide Probe Data, Journal of Safety Research (accepted for publication.)
3. Marshall, E., Shirazi, M., Shahlaee, A., & Ivan, J. N. (2023). Leveraging probe data to model speeding on urban limited access highway segments: Examining the impact of operational performance, roadway characteristics, and COVID-19 pandemic. Accident Analysis & Prevention, 187, 107038.
4. Marshall, E., Shirazi, M., & Ivan, J.N. (2023). COVID-19 and Transport Safety. Transport Review, Pages 518-543.
5. Islam, A. M., Shirazi, M., & Lord, D. (2023). Grouped Random Parameters Negative Binomial-Lindley for accounting unobserved heterogeneity in crash data with preponderant zero observations. Analytic Methods in Accident Research, 37, 100255.
6. Khodadadi*, A., Shirazi, M., Geedipally, S., & Lord, D. (2023). Evaluating alternative variations of Negative Binomial–Lindley distribution for modelling crash data. Transportmetrica A: transport science, 19(3), 2062480.
7. Sawtelle, A., Shirazi, M., Garder, P. E., & Rubin, J. (2023). Driver, roadway, and weather factors on severity of lane departure crashes in Maine. Journal of safety research, 84, 306-315.
8. Shahlaee, A., Shirazi, M., Marshall, E., & Ivan, J. N. (2022). Modeling the impact of the COVID-19 pandemic on speeding at rural roadway facilities in Maine using short-term speed and traffic count data. Accident Analysis & Prevention, 177, 106828.
9. Islam, A. M., Shirazi, M., & Lord, D. (2022). Finite mixture Negative Binomial-Lindley for modeling heterogeneous crash data with many zero observations. Accident Analysis & Prevention, 175, 106765.
10. Khodadadi*, A., Tsapakis, I., Shirazi, M, Das, S., & Lord, D. (2022). Derivation of the Empirical Bayesian method for the Negative Binomial-Lindley generalized linear model: Application in various safety analyses, Accident Analysis & Prevention, 170, 106638
11. Sawtelle, A., Shirazi, M., Garder, P. E., & Rubin, J. (2022). Exploring the impact of seasonal weather factors on frequency of lane-departure crashes in Maine. Journal of Transportation Safety & Security, 15(5), 445-466.
12. Shirazi, M., & Geedipally, S. R. (2022). A simulation analysis to explore when using a calibration function is preferred over a scalar factor for calibrating safety performance functions. Journal of Transportation Safety & Security, 15(4), 335-349.
13. Shirazi, M., Geedipally, S.R., & Lord, D. (2021). A Simulation Analysis to Study the Temporal and Spatial Aggregations of Safety Datasets with Excess Zero Observations. Transportmetrica A: Transport Science, 17(4), 1305-1317.
14. Wu, L., Dadashova, B., Geedipally, S., Pratt, M. P., & Shirazi, M. (2021). Using naturalistic driving study data to explore the association between horizontal curve safety and operation on rural two-lane highways. Journal of Transportation Safety & Security, 13(8), 896-913.
15. Geedipally, S. R., Pratt, M. P., Dadashova, B., Wu, L., & Shirazi, M. (2020). Examining the Feasibility of Using Naturalistic Driving Study Data for Validating Speed Prediction Models. Transportation Research Procedia, 48, 1084-1094.
16. Shirazi, M., & Lord, D. (2019). Characteristics-based heuristics to select a logical distribution between the Poisson-gamma and the Poisson-lognormal for crash data modelling. Transportmetrica A: Transport Science, 15(2), 1791-1803.
17. Pratt, M., Geedipally, S.R., Dadashova, B., Wu, L., & Shirazi, M. (2019). Familiar versus unfamiliar drivers on curves: naturalistic data study. Transportation Research Record, 2673(6), 225-235.
18. Shaon, M.R.R., Qin, X., Shirazi, M., Lord, D., & Geedipally, S.R. (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.
19. Shirazi, M., Dhavala, S.S., Lord, D., & Geedipally, S. R. (2017). A methodology to design heuristics for model selection based on characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB). Accident Analysis and Prevention, 107, pp.186-194.
20. Shirazi, M., Geedipally, S.R., & Lord D. (2017). A Monte-Carlo simulation analysis for evaluating the severity distribution functions (SDFs) calibration methodology and determining the minimum sample-size requirements. Accident Analysis and Prevention, 98, pp.303–311.
21. Shirazi, M., Aashtiani, H.Z., & Quadrifoglio, L. (2017). Estimating the minimal revenue tolls in large-scale roadway networks using the dynamic penalty function method. Computers and Industrial Engineering, 107, pp. 120-127.
22. Geedipally, S.R., Shirazi, M., & Lord, D. (2017). Exploring the need for region-specific calibration factors, Transportation Research Record, 2636, pp. 73–79.
23. Shirazi, M., Geedipally, S.R., & Lord, D. (2017). A procedure to determine when safety performance functions should be recalibrated. Journal of Transportation Safety and Security, 9(4), pp.457-469.
24. Shirazi, M., Lord, D., & Geedipally, S.R. (2016). Sample-size guidelines for recalibrating crash prediction models: Recommendations for the highway safety manual. Accident Analysis and Prevention, 93, pp. 160-168.
25. Shirazi, M., Lord, D., Dhavala, S.S., & Geedipally, S.R. (2016). A Semiparametric negative binomial generalized linear model for modeling over dispersed count data with a heavy tail: Characteristics and applications to crash data. Accident Analysis and Prevention, 91, pp. 10-18.
26. Khodakarami, M., Zhang, Y., Wang, B.X., Shirazi, M., & Dastgiri, M.S. (2016). Using a prospect theory approach to studying the car-following model. Advances in Human Aspects of Transportation. pp. 287-300.
27. Shirazi, M, & Aashtiani, H.Z. (2015). Solving the minimum toll revenue problem in real transportation networks. Optimization Letters, 9(6), pp.1187-1197.
