Outputs (56)

Applications of Knowledge Discovery in Massive Transportation Data: The Development of a Transportation Research Informatics Platform (TRIP). (2019)
Report
Majka, K., Nagler, E., James, A., Blatt, A., Pierowicz, J., Anastasopoulos, P. . C., & Fountnas, G. (2019). Applications of Knowledge Discovery in Massive Transportation Data: The Development of a Transportation Research Informatics Platform (TRIP). Federal Highway Administration

Transportation researchers and practitioners have access to unprecedented amounts of data but lack the tools to easily store, manipulate, and analyze these data. The Transportation Research Informatics Platform (TRIP) is an informatics-based system d... Read More about Applications of Knowledge Discovery in Massive Transportation Data: The Development of a Transportation Research Informatics Platform (TRIP)..

Effect of High Visibility Enforcement Programs on Aggressive Driving Behavior: An Empirical Analysis Using SHRP2 Naturalistic Driving Study (NDS) Data (2019)
Presentation / Conference Contribution
Fountas, G., Sonduru Pantangi, S., Anastasopoulos, P., Pierowicz, J., Majka, K., & Blatt, A. (2019, January). Effect of High Visibility Enforcement Programs on Aggressive Driving Behavior: An Empirical Analysis Using SHRP2 Naturalistic Driving Study (NDS) Data. Paper presented at Transportation Research Board 98th Annual Meeting, Washington DC, United States

This paper investigates the effect of High Visibility Enforcement on different types of aggressive driving behavior: speeding, tailgating, unsafe lane changes and ‘other’ aggressive driving behavior types (occurrence of not-yielding right-of-way and... Read More about Effect of High Visibility Enforcement Programs on Aggressive Driving Behavior: An Empirical Analysis Using SHRP2 Naturalistic Driving Study (NDS) Data.

Analysis of accident injury-severity outcomes: The zero-inflated hierarchical ordered probit model with correlated disturbances (2018)
Journal Article
Fountas, G., & Anastasopoulos, P. C. (2018). Analysis of accident injury-severity outcomes: The zero-inflated hierarchical ordered probit model with correlated disturbances. Analytic Methods in Accident Research, 20, 30-45

In accident injury-severity analysis, an inherent limitation of the traditional ordered probit approach arises from the a priori consideration of a homogeneous source for the accidents that result in a no-injury (or zero-injury) outcome. Conceptually... Read More about Analysis of accident injury-severity outcomes: The zero-inflated hierarchical ordered probit model with correlated disturbances.

Stationary and Time-Varying Factors Affecting Highway Accident Occurrence and Injury-Severity: Addressing Unobserved Heterogeneity with Alternate Random Parameters and Latent Class Models (2018)
Thesis
Fountas, G. Stationary and Time-Varying Factors Affecting Highway Accident Occurrence and Injury-Severity: Addressing Unobserved Heterogeneity with Alternate Random Parameters and Latent Class Models. (Thesis). University at Buffalo, The State University of New York. http://researchrepository.napier.ac.uk/Output/2671368

In contemporary accident research, unobserved heterogeneity is recognized as one of the most challenging statistical modeling misspecification issues.Unobserved heterogeneity (i.e.,unobserved characteristics varying systematically across ob... Read More about Stationary and Time-Varying Factors Affecting Highway Accident Occurrence and Injury-Severity: Addressing Unobserved Heterogeneity with Alternate Random Parameters and Latent Class Models.

Analysis of accident injury-severities using a correlated random parameters ordered probit approach with time variant covariates (2018)
Journal Article
Fountas, G., Anastasopoulos, P. C., & Abdel-Aty, M. (2018). Analysis of accident injury-severities using a correlated random parameters ordered probit approach with time variant covariates. Analytic Methods in Accident Research, 18, 57-68. https://doi.org/10.1016/j.amar.2018.04.003

This paper employs a correlated random parameters ordered probit modeling framework to explore time-variant and time-invariant factors affecting injury-severity outcomes in single-vehicle accidents. The proposed approach extends traditional random pa... Read More about Analysis of accident injury-severities using a correlated random parameters ordered probit approach with time variant covariates.

Analysis of vehicle accident-injury severities: A comparison of segment- versus accident-based latent class ordered probit models with class-probability functions (2018)
Journal Article
Fountas, G., Anastasopoulos, P. C., & Mannering, F. L. (2018). Analysis of vehicle accident-injury severities: A comparison of segment- versus accident-based latent class ordered probit models with class-probability functions. Analytic Methods in Accident Research, 18, 15-32. https://doi.org/10.1016/j.amar.2018.03.003

Using information from 1990 single-vehicle accidents that occurred between 2011 and 2013 in the state of Washington, the injury severity level of the most severely injured vehicle occupant is studied using two latent class modeling approaches: segmen... Read More about Analysis of vehicle accident-injury severities: A comparison of segment- versus accident-based latent class ordered probit models with class-probability functions.

Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach (2018)
Journal Article
Fountas, G., Sarwar, M. T., Anastasopoulos, P. C., Blatt, A., & Majka, K. (2018). Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach. Accident analysis and prevention, 113, 330-340. https://doi.org/10.1016/j.aap.2017.05.018

Traditional accident analysis typically explores non-time-varying (stationary) factors that affect accident occurrence on roadway segments. However, the impact of time-varying (dynamic) factors is not thoroughly investigated. This paper seeks to simu... Read More about Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach.

Effectiveness of various public private partnership pavement rehabilitation treatments: A big data informatics survival analysis of pavement service life (2017)
Report
David, D., Fountas, G., Sarwar, M. T., Eker, U., Akpinar, S., & Anastasopoulos, P. C. (2017). Effectiveness of various public private partnership pavement rehabilitation treatments: A big data informatics survival analysis of pavement service life. US Department of Transportation Office of the UTC Program

Past research efforts have used a wide variety of methodological approaches to analyze pavement performance indicators, pavement rehabilitation treatments, and pavement service life. Using big data informatics methods, the intent of this study is to... Read More about Effectiveness of various public private partnership pavement rehabilitation treatments: A big data informatics survival analysis of pavement service life.

Simultaneous estimation of discrete outcome and continuous dependent variable equations: A bivariate random effects modeling approach with unrestricted instruments (2017)
Journal Article
Sarwar, M. T., Fountas, G., & Anastasopoulos, P. C. (2017). Simultaneous estimation of discrete outcome and continuous dependent variable equations: A bivariate random effects modeling approach with unrestricted instruments. Analytic Methods in Accident Research, 16, 23-34. https://doi.org/10.1016/j.amar.2017.05.002

This paper proposes a novel methodology to simultaneously model discrete outcome (binary) and continuous dependent variables. The proposed modeling framework addresses unobserved heterogeneity by accounting for both panel effects, and for contemporan... Read More about Simultaneous estimation of discrete outcome and continuous dependent variable equations: A bivariate random effects modeling approach with unrestricted instruments.

A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities (2017)
Journal Article
Fountas, G., & Anastasopoulos, P. C. (2017). A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities. Analytic Methods in Accident Research, 15, 1-16. https://doi.org/10.1016/j.amar.2017.03.002

This study uses highway accident data collected in the State of Washington, between 2011 and 2013, to study the factors that affect accident injury-severities. To account for the fixed thresholds limitation of the traditional ordered probability mode... Read More about A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities.