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- W622579144 abstract "This paper investigates the effectiveness of lowering speed limits in reducing vehicle operating speeds. The authors employ a full Bayes before-after approach using a group of comparison sites. The proposed methodology allows analyzing data using hourly observations and hence the entire daily profile of speed is considered. Furthermore, it accounts for the entire distribution of speed in contrast to the traditional approach of considering only a point estimate such as 85th 8 percentile. Different reference speeds were used to examine variations in the treatment effectiveness in terms of speeding rate and frequency. In addition to comparing rates of vehicles exceeding reference speeds of 40 km/h and 50 km/h for normal speeding incidents, the authors verified how the implemented treatment affected occurrences of excessive speeding. To model operating speeds, two Bayesian generalized mixed linear models were utilized, which have the advantage of being able to address the heterogeneity issue in observations and efficiently capture any potential intra-site correlations. A variety of site characteristics, temporal variables, and environmental factors were considered. The analyses indicated that variables like lane width and night hour had an increasing effect on the occurrence of normal speeding incidents. While one-way and lane width had an increasing effect on excessive speeding, evening hour had a decreasing effect. This study concluded that although the treatment was effective with respect to speed references of 40km/h and 50 km/h, its effectiveness was not significant with respect to excessive speeding. Therefore, caution must be taken in drawing conclusions about the effectiveness of speed limit reduction." @default.
- W622579144 created "2016-06-24" @default.
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- W622579144 date "2014-01-01" @default.
- W622579144 modified "2023-09-23" @default.
- W622579144 title "Effects of Lowering Speed Limits in Urban Areas: A Bayesian Perspective" @default.
- W622579144 hasPublicationYear "2014" @default.
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