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Bhagwant Persaud

Researcher at Ryerson University

Publications -  188
Citations -  7640

Bhagwant Persaud is an academic researcher from Ryerson University. The author has contributed to research in topics: Crash & Poison control. The author has an hindex of 48, co-authored 185 publications receiving 7141 citations.

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Safety Effect of Roundabout Conversions in the United States: Empirical Bayes Observational Before-After Study

TL;DR: A before-after study was conducted using the empirical Bayes procedure, which accounts for regression to the mean and traffic volume changes that usually accompany conversion of intersections to roundabouts and suggests that roundabout installation should be strongly promoted as an effective safety treatment for intersections.
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Accident Prediction Models With and Without Trend: Application of the Generalized Estimating Equations Procedure

TL;DR: An application is presented of a generalized estimating equations (GEE) procedure to develop an APM that incorporates trend in accident data and the GEE model incorporating the time trend is shown to be superior to models that do not accommodate trend and/or the temporal correlation in accidentData.
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Exploration of the Breakdown Phenomenon in Freeway Traffic

TL;DR: The research on which this paper is based was aimed at exploring in more detail the implications of metering traffic flow at levels below that at which a breakdown occurs, and it is shown that 1-min median lane flows that are 20 percent larger than queue discharge flows have only a 10 percent probability of breakdown.
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Empirical Bayes before–after safety studies: Lessons learned from two decades of experience and future directions

TL;DR: This paper is to capitalize on experience gained from two decades of conducting EB studies around the world to illustrate that the EB methodology, if properly undertaken, produces results that could be substantially different and less biased than those from more conventional types of studies.
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Development of planning level transportation safety tools using Geographically Weighted Poisson Regression.

TL;DR: This article investigated the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors, using the Geographically Weighted Poisson Regression (GWPR) modeling technique.