Tawfiq Sarwar

Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach

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 simultaneously identify pre-crash stationary and dynamic factors of accident occurrence, while accounting for unobserved heterogeneity. Using highly disaggregate information for the potential dynamic factors, and aggregate data for the traditional stationary elements, a dynamic binary random parameters (mixed) logit framework is employed. With this approach, the dynamic nature of weather-related, and driving- and pavement-condition information is jointly investigated with traditional roadway geometric and traffic characteristics. To additionally account for the combined effect of the dynamic and stationary factors on the accident occurrence, the developed random parameters logit framework allows for possible correlations among the random parameters. The analysis is based on crash and non-crash observations between 2011 and 2013, drawn from urban and rural highway segments in the state of Washington. The findings show that the proposed methodological framework can account for both stationary and dynamic factors affecting accident occurrence probabilities, for panel effects, for unobserved heterogeneity through the use of random parameters, and for possible correlation among the latter. The comparative evaluation among the correlated grouped random parameters, the uncorrelated random parameters logit models, and their fixed parameters logit counterpart, demonstrate the potential of the random parameters modeling, in general, and the benefits of the correlated grouped random parameters approach, specifically, in terms of statistical fit and explanatory power.

Project Discrepancies in Roadway Construction and Preservation: A Statistical Analysis of Public–Private Partnership Contract Types in the US

At the planning stage of a roadway construction or preservation project, public agencies face a crucial challenge; to adopt and implement the appropriate contractual framework that can minimize the anticipated project discrepancies, on the basis of project-specific conditions. Focusing on Public-Private Partnerships (PPP), a deeper understanding of the factors that affect each type of discrepancy can assist public agencies in thoroughly evaluating and comparing PPP options. This paper seeks to provide an empirical but comprehensive analysis on PPP-specific project discrepancies, by identifying influential factors that significantly affect cost savings, cost overrun, change orders, and time delays in roadway projects. Using data from 645 PPP projects implemented in the USA between 1996 and 2011, seven popular PPP contracting approaches in the USA were considered in the analysis, and a number of random parameters linear and non-linear statistical models were estimated by PPP approach. The results demonstrate that PPP-specific attributes such as project cost, size, types of constituent activities, and expected duration, have mixed effects on the occurrence and the magnitude of each type of discrepancy.