Systematic identification of high crash locations
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2001-05-01
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Abstract:The objective of this project is to develop tools and procedures by which Iowa engineers can identify potentially hazardous roadway locations and designs, and to demonstrate the utility of these tools by developing candidate lists of high crash locations in the state. The initial task was to build an integrated database to facilitate the tools and procedures. The Iowa Department of Transportation (Iowa DOT) Geographic Information Management Systems (GIMS) and Geographic Information System Accident Analysis and Location System (GIS-ALAS) databases were integrated with available digital imagery. The GIMS database contains roadway characteristics, such as lane width, surface and shoulder type, and traffic volume, for all public roads. GIS-ALAS records contain crash data for crashes occurring on public roads during the past 10 years. This data includes vehicles, road conditions, drivers, and crash severity. Using the GIMS and GIS-ALAS databases, high crash locations and relationships between crash rates and selected roadway design characteristics were identified. As expected, results indicate that head-on crash rates are higher on lower classification (e.g., local and farm to market) highways. Rates are also affected by speed limit, terrain, shoulder width, shoulder type and the pavement condition (international roughness index). The analysis also indicates that fixed-object crash rates are higher on lower classification highways. In addition, interstate highways, highway segments in flat and rolling terrain tend to have higher crash rates compared to segments in hilly terrain. Similarly, segments with asphalt cement concrete pavement surface tend to experience higher crash rates compared to other types of surfaces. Segments with paved shoulders have lower fixed-object crash rates, and segments with no median barrier tend to have higher fixed-object crash rates. Analysis of curve-related crash data indicates that the degree of curvature has a direct impact on crash rates on horizontal curves. The project produced the following items: 1. curve database for Iowa, with radii and length attributes, 2. procedures for identifying high crash locations of five types, 3. statistical models of the relationship between geometric features and crash rates, and 4. candidate lists (maps and tables) for improvement (Iowa top 30 list) for five problem types.
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