Description: <div style="text-align:Left;"><div><div><p><span style="font-weight:bold;">General Description of Systemic Safety Analysis</span></p><p><span><span>The systemic safety approach “involves widely implemented improvements based on high-risk roadway features correlated with specific severe crash types. The approach provides a more comprehensive method for safety planning and implementation that supplements and complements traditional site analysis.” The systemic approach gives agencies another tool to address safety by allowing them to consider the risk of a site instead of its crash history. The general attributes of a systemic safety analysis include:</span></span></p><p><span style="font-weight:bold;">Identifying focus crash types and risk factors</span></p><ul><li><p><span><span>Agencies need to identify a crash type to focus on, based on either statewide data or on an area identified in prior planning activities such as the </span><span>State Strategic Highway Safety Plan (SHSP). </span><span>Often the crashes associated with a focused crash types are randomly distributed across a network with few locations experiencing a cluster of crashes. For this analysis the focus was on bicyclist and pedestrian involved crashes.</span></span></p></li><li><p><span style="font-weight:bold;">Defining risk factors</span></p></li><li><p><span><span>After identifying a focus crash type, agencies associate those crashes with roadway or intersection characteristics. This association helps identify roadway characteristics that are correlated with a higher frequency or rate of that crash type. These characteristics, also known as risk factors, can be used to identify and prioritize similar locations where no crash history currently exists. </span></span></p></li><li><p><span style="font-weight:bold;">Screening and prioritizing the network</span></p></li><li><p><span><span>Risk factors (or roadway characteristics) are typically scored and weighted by agencies. This process of prioritizing characteristics allows agencies to take that information in combination and find areas within their roadway network that have higher concentrations of risk factors.</span></span></p></li><li><p><span><span>The resulting analysis identified roadways and intersections that have the greatest risk, regardless of existing crash history at those locations. Agencies can use this information to help select appropriate countermeasures and prioritize projects. </span></span></p></li></ul><p><span style="font-weight:bold;">Data Used in this analysis</span></p><ul><li><p><span style="font-weight:bold;">Crash Data</span></p></li></ul><ul><li><p><span><span>Ten years of crash data from 2009-2018 was used in this analysis. Only non-motorists crashes involving pedestrians, skaters, those using a personal conveyance, wheelchair occupants, bicyclists, and bicycle passengers were included in the analysis. Data as accessed July 8th, 2019. </span></span></p></li></ul><ul><li><p><span style="font-weight:bold;">Intersection Data</span></p></li></ul><ul><li><p><span>All paved intersections within the state were analyzed by utilizing the department’s intersection database. The only intersections not included in this analysis were intersections on unpaved roads and intersections with more unpaved legs than paved. The intersection database was developed by Iowa State University’s Institute for Transportation (InTrans) from 2013 to 2017 using roadway data, aerial imagery, and Google Streetview images. The version of the database used in this analysis was last updated on April 2017. </span></p></li></ul><p><span></span></p><p><span style="font-weight:bold;">Feature Class Description</span></p><p><span>The intersection data contained in this feature class includes all of the intersections within the state of Iowa that had at least half of the legs paved. Each intersection has been analyzed according to the general process described above and for this particular feature class the focus was on pedestrians. The primary output of this analysis was a composite score from 0-100 for each intersection. This score indicates the relative risk of the intersection as it relates to the attributes used in this analysis. The lower the composite score the higher the risk. Higher composite score rankings suggest less risk at those sites. For rural pedestrian intersections the minimum composite score was 20, the max was 87.1, and the average was 60.2. For the urban pedestrian score the minimum composite score was 22.3, the maximum 100, and the average was 83.8.</span></p><p><span></span></p></div></div></div>
Copyright Text: Iowa Department of Transportation - Systems Planning Bureau
Description: <div style="text-align:Left;"><div><div><p><span style="font-weight:bold;">General Description of Systemic Safety Analysis</span></p><p><span>The systemic safety approach “involves widely implemented improvements based on high-risk roadway features correlated with specific severe crash types. The approach provides a more comprehensive method for safety planning and implementation that supplements and complements traditional site analysis.” The systemic approach gives agencies another tool to address safety by allowing them to consider the risk of a site instead of its crash history. The general attributes of a systemic safety analysis include:</span></p><p><span style="font-weight:bold;">Identifying focus crash types and risk factors</span></p><ul><li><p><span>Agencies need to identify a crash type to focus on, based on either statewide data or on an area identified in prior planning activities such as the </span><span>State Strategic Highway Safety Plan (SHSP)</span><span>. Often the crashes associated with a focused crash types are randomly distributed across a network with few locations experiencing a cluster of crashes. For this analysis the focus was on bicyclist and pedestrian involved crashes.</span></p></li><li><p><span style="font-weight:bold;">Defining risk factors</span></p></li><li><p><span>After identifying a focus crash type, agencies associate those crashes with roadway or intersection characteristics. This association helps identify roadway characteristics that are correlated with a higher frequency or rate of that crash type. These characteristics, also known as risk factors, can be used to identify and prioritize similar locations where no crash history currently exists. </span></p></li><li><p><span style="font-weight:bold;">Screening and prioritizing the network</span></p></li><li><p><span>Risk factors (or roadway characteristics) are typically scored and weighted by agencies. This process of prioritizing characteristics allows agencies to take that information in combination and find areas within their roadway network that have higher concentrations of risk factors.</span></p></li><li><p><span>The resulting analysis identified roadways and intersections that have the greatest risk, regardless of existing crash history at those locations. Agencies can use this information to help select appropriate countermeasures and prioritize projects. </span></p></li></ul><p><span style="font-weight:bold;">Data Used in this analysis</span></p><ul><li><p><span style="font-weight:bold;">Crash Data</span></p></li></ul><ul><li><p><span>Ten years of crash data from 2009-2018 was used in this analysis. Only non-motorists crashes involving pedestrians, skaters, those using a personal conveyance, wheelchair occupants, bicyclists, and bicycle passengers were included in the analysis. Data as accessed July 8th, 2019. </span></p></li></ul><ul><li><p><span style="font-weight:bold;">Roadway data and Jurisdictional data</span></p></li></ul><ul><li><p><span>Roadway data was extracted from the Road Asset Management System (RAMS). The analysis included all paved roads within the state. Attributes included in the dynamic segmentation included number of lanes, average annual daily traffic (AADT), route name, shoulder width, shoulder type, shoulder rumble, speed limit, parking type, and median type. Jurisdictional data was also spatially joined to all the segments in the analysis including city, county, Regional Planning Agency (RPA), and Metropolitan Planning Organization (MPO). Roadways with minimum speed limits were eliminated from this analysis because pedestrian and bicyclist are prohibited from using facilities with minimum speed limits. The most recent access of this data was from September 20th, 2019. </span></p></li></ul><p style="margin:0 0 14 0;"><span style="font-weight:bold;">Feature Class Description</span></p><p style="margin:0 0 14 0;"><span>The roadway segment data contained in this feature class includes all of the paved roadways within the state of Iowa. Each segment has been analyzed according to the general process described above and for this particular feature class the focus was on pedestrians. The primary output of this analysis was a composite score from 0-100 for each roadway segment. This score indicates the relative risk of the segment as it relates to the attributes used in this analysis. The lower the composite score the higher the risk. Higher composite score rankings suggest less risk at those sites. For rural pedestrian segments the minimum composite score was 24, the max was 100, and the average was 79.2. For the urban pedestrian score the minimum composite score was 17.5, the maximum 95, and the average was 60.3.</span></p><p><span></span></p></div></div></div>
Copyright Text: Iowa Department of Transportation - Systems Planning Bureau
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