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Title:Traffic Safety Vulnerability Information Platform for Highways in Mountainous Areas Using Geospatial Multimedia Technology
Authors:Suren Chen, Juhua Liu, Feng Chen, and Jun Wu
University:Colorado State University
Publication Date:Dec 2008
Report #:MPC-08-209
Project #:MPC-292
TRID #:01123424
Keywords:acceleration (mechanics), crosswinds, field studies, geographic information systems, mountain roads, multimedia, traffic safety, trucking safety, trucks
Type:Research Report – MPC Publications


An integrated mobile testing study that utilized a large truck equipped with various testing equipment was conducted on Interstate I-70 in Colorado. The field study integrated wind measurement, vehicle dynamic monitoring and geospatial multimedia technology on a real-time and synchronized basis. Essential multi-type data was collected in both time and spatial domains for further investigations of wind characterizations and the safety performance of large trucks under crosswinds, in complicated topographic conditions and other environmental conditions. Environmental geospatial multimedia information for transportation safety has become a very important information source with data integration from both DOT and drivers' perspective in terms of planning, precise decision-making and management. Drivers can benefit from the geospatial multimedia information of road environments in terms of driving safety and confidence. Based on the field testing results, a framework for a traffic vulnerable information system was developed, and the geospatial multimedia technology was integrated with environmental condition and just emerged in transportation engineering field and Web-based platform to assist transportation management and drivers. This study implemented Video Mapping System (VMS) technology along the I-70 mountain corridor, measured wind speeds in three dimensions and accelerations in two dimensions, and developed a Web-based geospatial multimedia database with embedded wind speeds and accelerations as environmental-related georeferenced vulnerable traffic information at selected feature points in the testing route.

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