Roundabouts have been widely used in the UK on all road classes, as they are generally considered safer than other types of intersections. The objective of this study is to examine geometric and traffic characteristics and their influence on accident numbers.The study comprises 70 roundabouts (284 approaches). The data used included all recorded vehicle accidents, geometric, and traffic characteristics for whole roundabouts, within the circulatory lanes, and at approaches to the roundabouts. Random-parameters negative binomial count data models were used to estimate model parameters and the models were compared with fixed-parameters negative binomial count data models.The random-parameters models provide better goodness of fit and more variables were found to be significant, relative to the fixed-parameters model. Total approach traffic, truck percentage, entry width, inscribed circle diameter, number of lanes, and presence of traffic signals were found as significant variables influencing accident occurrences.Keywords: Roundabout, accidents, random-parameters, fixed-parameters Kamla, Parry, Dawson 2 INTRODUCTIONRoundabout numbers continue to rise in countries and regions where they are already common, and especially, they are earning popularity in places where there were few roundabouts in the past. With respect to traffic operations and safety, roundabouts are often favoured over other intersection types. The use of roundabouts can improve safety by reducing or changing conflict types, reducing accident severity, and leading drivers to reduce speeds (1) (2) (3) (4). Various studies have analysed the safety of roundabouts, with a significant observed reduction in the number of accidents when intersections were converted to roundabouts (5) (6) (7) (8) (9) (10) (11) (12).Geometric layout, operational analysis and safety evaluation, are significant recurring requirements for roundabout design. Small modifications in geometry can lead to considerable changes in the safety and/or operational performance of roundabouts. The Highway Safety Manual (HSM) (13) uses traffic volume as a major input into the base condition safety performance function. Roundabouts, as substitute intersections, are likely to exhibit a similar traffic volume influence on their anticipated safety performance. Many studies have been undertaken to predict accident models depending on geometric and traffic variables using count data (Poisson or negative binomial models) (14) (15) (16) (17) (18) (19) (20). However, these studies assumed that variables (geometric and traffic) are constant across the observations (roundabouts). In some cases constraining the parameters to be constant when they actually vary across observations could lead to inconsistent and biased parameter estimates (21). However, there is potential by allowing some or all parameters to vary across observations, to account for heterogeneity across observations; for this reason, later research on general accident models (not at roundabouts) has used random-parameters; random...
In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous accident history. However, as accident rates have continued to fall, this approach has become problematic as accident 'black spots' have been treated and the number of accidents at any individual site has fallen, making previous accident history a less reliable indicator of future accident risk. Another way of identifying sites of higher accident risk might be to identify near-miss accidents (where an accident nearly happened but was avoided). The principal aim of this paper is to analyze potentially unsafe truck driving conditions from counts of Harsh Braking Incidents (HBIs) at roundabouts and compare the results to similar, previous studies of accident numbers at the same sites, to explore if HBIs can be studied as a surrogate for accidents. This is achieved by processing truck telematics data with geo-referenced incidents of harsh braking. Models are then developed to characterise the relationships between truck HBIs and geometric and traffic variables. These HBIs are likely to occur more often than accidents and may, therefore, be useful in identifying sites with high accident risk. Based on the results of this study, it can be concluded that HBIs are influenced by traffic and geometric variables in a similar way to accidents; therefore they may be useful in considering accident risk at roundabouts. They are a source of higher volumes of data than accidents, which is important in considering changes or trends in accident risk over time. The results showed that random-parameters count data models provide better goodness of fit compared to fixed-parameters models and more variables were found to be significant, giving a better prediction of events.
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