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Washington State requires large employers in its nine most populous counties to encourage their employees to reduce commuting vehicle trips and to monitor progress by surveying employees. The monitoring requirement yields roughly 250,000 surveys every 2 years. Analysis of the survey results for 1999 and previous years estimated that the program removed an average of 18,500 vehicles from the road during the morning peak in 1999, with 12,600 of these in the Seattle metropolitan area. Information from the surveys was used to construct an origin-destination table for these trips, and the table was then used in a four-step modeling process to estimate the corridors and links that realized the greatest effect of the trip-reduction program. The modeling compared a baseline, which assumed effects of the trip-reduction program, with a case in which trips removed were added back into the trip tables. Results indicate that the trip-reduction program has measurable effects on traffic volumes and delay, both areawide and in specific corridors. The analysis is unique in having these types of data on which to draw for a metropolitan area whose modeling system can use them.

This individual-level case control study analyzed the risk of occurrence of a pedestrian–motor vehicle collision at a given location on a state route in King County, Washington. With the full sample of collisions (1999-2004), binomial logit models estimated the odds of collision occurrence as related to the road and the neighborhood environments and adjusting for exposure. Separate models were run for SR-99, the principal transregional arterial with four-plus lanes ( n = 826), and for all the other state routes ( n = 1,602). The strongest significant correlates of the risk of collision occurrence were the presence of crosswalks with or without traffic signals, the facility's number of lanes, and the presence of nearby retail uses. Also positively significant were the number of traffic signals and the street-block size near the location and being located outside the city of Seattle. Exposure variables including road-level measures such as average daily traffic and posted speed and neighborhood-level measures such as the number of residential units and bus ridership were significant in at least one of the models. Employment density appeared to be an unreliable measure of exposure. Other pedestrian activity generators such as educational facilities were not significantly associated with the risk of collision occurrence. The strong significance of crosswalks, whether signalized or not, indicated that engineering approaches to safety should likely be complemented by education- and enforcement-based measures. Similarly, facilities in areas with concentrations of retail should become the targets of future safety programs.

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