Issue link: http://uwashington.uberflip.com/i/742071
21 2014-2015 Annual Report • Project:Guidelines for Pervious Concrete Sidewalks, Parking Lots, and Shared-Use Paths to Improve Drivers, Bikers, and Pedestrian Safety • PI: Somayeh Nassiri (WSU), snassiri@wsu.edu Pervious concrete has been recommended as one of the Best Management Practices (BMP) by the United States' Environmental Protection Agency (EPA) and other agencies for stormwater and runoff management. Runoff and snowmelt control, vehicle pollutant reduction, heat-island effect reduction, water spray/splash and hydroplaning reduction, and recharging of groundwater supplies are some of the firsthand advantages of pervious concrete over traditional mixtures. Such advantages have made pervious concrete a desirable product for various municipal applications such as bike lanes, pedestrian walkways, sidewalks, parking lots and low-volume roadways. Different municipalities in the Pacific Northwest have been experimenting with replacing traditional concrete with pervious concrete for such applications. Paramount to its growth in popularity is research on its possibly enhanced safety and skid-resistance in parking lots and bike lane applications and slip-resistance for sidewalks. Additional research is needed to identify the best winter maintenance practices to maintain safety while maintaining acceptable performance. Thus objectives of this study are to: (1) test safety aspects of pervious concrete sidewalks/parking lots/bike lanes in winter conditions, and (2) develop additional best-practice guidance for winter maintenance of pervious concrete installations. • Project: Developing a clustering-based empirical Bayes analysis method for hotspot identification • PI: Yajie Zou (UW), yinhai@uw.edu The identification of crash hotspot sites, or hazardous locations, is the first step in any overall safety management process. One widely applied approach to this task is the popular empirical Bayes (EB) method. Although the EB method has several advantages, there are a number of issues associated with the methodology which may limit its widespread application. One flaw is that the EB method depends largely on the selection of the reference population or grouping of similar sites, and the definition of "similar" is a somewhat open question. Given that the specification of correct reference groups is critical for the accuracy of the EB methodology, the primary objective of this research will examine different clustering algorithms and develop a complete procedure to automatically identify appropriate reference groups for the EB analysis. We will develop an analysis tool to automate implementation of the clustering- based EB method. The purpose of this javascript-based tool is to provide a user-friendly platform, which can be easily operated by transportation safety analysts to identify sites with potential for safety treatments.