Dr. A.P. (Amir Pooyan) Afghari


Amir is a postdoc in transport safety and human factors at the Safety and Security Science section of the Technology, Policy, and Management faculty at TU Delft. He is mainly involved in the iDreams project funded by the European Union’s Horizon 2020 Research and Innovation Programme.
Amir completed his PhD in transport safety at the University of Queensland in Brisbane, Australia. Prior to joining TU Delft, he worked at several research centres around the world such as Queensland University of Technology (Australia), University of Queensland (Australia), McGill University (Canada), École Polytechnique Montréal (Canada), Concordia University (Canada) and University of Wuppertal (Germany).


Amir has been involved in globally developed research projects for almost a decade. He has published several peer-reviewed articles in the leading journals in transport engineering and social science such as Analytic Methods in Accident Research, Accident Analysis and Prevention, Traffic Injury Prevention, Sustainable Cities and Society, and Transportation Research Records. Some examples of his research in transport safety include: road users’ receptivity towards autonomous vehicles, vehicle occupants’ seat-belt use, distracted drivers’ risk-compensating behaviour, missing data analysis in transport safety, Bayesian inference in transport safety, analysis of crash data with excess zero
observations, crash blackspot identification, bicycle sharing systems, and automated data analytics for vulnerable road users.  Amir’s research interest focuses on advanced statistical and econometric methods in transport safety, driver behaviour and human factors. He is also interested in the applications of statistical and econometric models in other fields of transport engineering and social science including transport health, travel behaviour, and travel demand.

Washington S, Afghari A, Haque M, (2018) Detecting high-risk accident locations, Safe mobility: Challenges, methodology and solutions (Transport and Sustainability, Volume 11) p351-382

Oviedo-Trespalacios O, Afghari A, Haque S, (2020) A hierarchical Bayesian multivariate ordered model of distracted drivers’ decision to initiate riskcompensating behaviour, Analytic Methods in Accident Research p1-46
Afghari A, Washington S, Prato C, Haque M, (2019) Contrasting case-wise deletion with multiple imputation and latent variable approaches to dealing with missing observations in count regression models, Analytic Methods in Accident Research p1-19
Afghari A, Haque M, Washington S, Smyth T, (2019) Effects of globally obtained informative priors on Bayesian safety performance functions developed for Australian crash data, Accident Analysis and Prevention p55-65
Shaon M, Qin X, Afghari A, Washington S, Haque M, (2019) Incorporating behavioral variables into crash count prediction by severity: A multivariate multiple risk source approach, Accident Analysis and Prevention p277-288
Abolhassani L, Afghari A, Borzadaran H, (2019) Public preferences towards bicycle sharing system in developing countries: The case of Mashhad, Iran, Sustainable Cities and Society p763-773
Afghari A, Washington S, Haque M, Li Z, (2018) A comprehensive joint econometric model of motor vehicle crashes arising from multiple sources of risk, Analytic Methods in Accident Research p1-14
Afghari A, Haque M, Washington S, (2018) Applying fractional split model to examine the effects of roadway geometric and traffic characteristics on speeding behavior, Traffic Injury Prevention p860-866
Afghari A, Haque M, Washington S, Smyth T, (2016) Bayesian latent class safety performance function for identifying motor vehicle crash black spots, Transportation Research Record p90-98

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