Of late, there has been a considerable volume of empirical research on freeway operations during periods of high flow. Part of the motivation for this realm of research is the attractive possibility of increasing flow and speed by preventing breakdown in congested operations. This possibility has been fueled by observations of a “capacity drop,” wherein the discharge flow from the resulting queue is smaller than those observed before breakdown. 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. From this perspective, the nature of precongestion flows is investigated empirically to determine the potential gains from such a policy. The most important contribution is an examination of the likelihood of success of such metering by establishing the probability of breakdown at various traffic flow levels. It is shown, for example, that 1-min median lane flows that are 20 percent larger than queue discharge flows have only a 10 percent probability of breakdown and that 1-min flows equal to the mean queue discharge flows have a negligible probability of breakdown. These results not only have practical significance but also are useful for improving the efficiency of freeway simulation models.

Modern roundabouts are designed to control traffic flow at intersections without the use of stop signs or traffic signals. U.S. experience with modern roundabouts is rather limited to date, but in recent years there has been growing interest in their potential benefits and a relatively large increase in roundabout construction. This interest has created a need for data regarding the safety effect of roundabouts. Changes in motor vehicle crashes following conversion of 23 intersections from stop sign and traffic signal control to modern roundabouts are evaluated. The settings, located in seven states, are a mix of urban, suburban, and rural environments with the urban sample consisting of both single-lane and multilane designs and the rural sample consisting of only single-lane designs. 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. For the 23 intersections combined, this procedure estimated highly significant reductions of 40 percent for all crash severities combined and 80 percent for all injury crashes. Reductions in the numbers of fatal and incapacitating injury crashes were estimated to be about 90 percent. In general, the results are consistent with numerous international studies and suggest that roundabout installation should be strongly promoted as an effective safety treatment for intersections. Because the empirical Bayes approach is relatively new in safety analysis, the potential of this methodology in the evaluation of safety measures is demonstrated.

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A series of macrolevel prediction models that would estimate the number of accidents in planning zones in the city of Toronto, Ontario, Canada, as a function of zonal characteristics were developed. A generalized linear modeling approach was used in which negative binomial regression models were developed separately for total accidents and for severe (fatal and nonfatal injury) accidents as a function of socio-economic and demographic, traffic demand, and network data variables. The variables that had significant effects on accident occurrence were the number of households, the number of major road kilometers, the number of vehicle kilometers traveled, intersection density, posted speed, and volume-capacity ratio. The geographic weighted regression approach was used to test spatial variations in the estimated parameters from zone to zone. Mixed results were obtained from that analysis.

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The identification of sites requiring investigation for possible safety treatment is one of the most important aspects of infrastructure safety management and has been the subject of considerable research aimed at improving the efficiency of the process. The more recent techniques use the empirical Bayes (EB) method for estimating the safety of specific sites. A refinement of the EB method that is conceptually sound and inherently simple to apply is the focus of this research. With this refinement, the EB estimate of the safety of a site is compared with its expected safety to determine the potential for safety improvement, which forms the basis for ranking sites for safety investigation. A comparative evaluation is provided of the proposed method against other EB methods and the more conventional ones, with data for signalized intersections and two-lane rural highway sections. The refined EB method is shown to be comparatively efficient.