Description: <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The top 200 locations where reported collisions occurred at intersections have been identified. The crash cluster analysis methodology for the top intersection clusters uses a fixed meter search distance of 25 meters (82 ft.) to merge crash clusters together. This analysis was based on crashes where a police officer specified one of the following junction types: Four way intersection, T-intersection, Y-intersection, five point or more. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). The clusters were reviewed in descending EPDO order until 200 locations were obtained. The clustering analysis used crashes from the three year period from 2014-2016. The area encompassing the crash cluster may cover a larger area than just the intersection so it is critical to view these spatially.</SPAN></P></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Highway Division Safety Group
Name: Top 5% Intersection Crash Clusters 2019-2021
Display Field: DistrictName
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top locations where reported collisions occurred at intersections have been identified. The crash cluster analysis methodology for the top intersection clusters uses a fixed meter search distance of 25 meters (82 ft.) to merge crash clusters together. This analysis was based on crashes where a police officer specified one of the following junction types: Four way intersection, T-intersection, Y-intersection, five point or more. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). The clustering analysis used crashes from the three year period from 2019-2021. The area encompassing the crash cluster may cover a larger area than just the intersection so it is critical to view these spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Office of Planning
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top locations where reported collisions occurred between bicyclists and motor vehicles have been identified. The crash cluster analysis methodology for the top bicyclist clusters uses a fixed meter search distance of 100 meters (328 ft.) to merge crash clusters together. Located crashes between motor vehicles and bicyclists were identified by using the non-motorist type code within the CDS database (which may yield different results from using most harmful event, first harmful event, or sequence of events data fields). Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. However, because of the relatively small number of reported bicyclists crashes in the crash data file, the clustering analysis used crashes from the ten year period from 2012-2021. Additionally, due to the larger geographic area encompassed by the bicyclist crash clusters, it was difficult to name them so they were left unnamed but can be viewed spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Office of Planning
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top locations where reported collisions occurred between pedestrians and motor vehicles have been identified. The crash cluster analysis methodology for the top pedestrian clusters uses a fixed meter search distance of 100 meters (328 ft.) to merge crash clusters together. Located crashes between motor vehicles and pedestrians were identified by using the non-motorist type code as well as first harmful events and most harmful events within the CDS database. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). However, because of the relatively small number of reported pedestrian crashes in the crash data file, the clustering analysis used crashes from the ten year period from 2012-2021. Additionally, due to the larger geographic area encompassed by the pedestrian crash clusters, it was difficult to name them so they were left unnamed but can be viewed spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Office of Planning
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top 200 locations where reported collisions occurred at intersections have been identified. The crash cluster analysis methodology for the top intersection clusters uses a fixed meter search distance of 25 meters (82 ft.) to merge crash clusters together. This analysis was based on crashes where a police officer specified one of the following junction types: Four way intersection, T-intersection, Y-intersection, five point or more. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). The clusters were reviewed in descending EPDO order until 200 locations were obtained. The clustering analysis used crashes from the three year period from 2017-2019. The area encompassing the crash cluster may cover a larger area than just the intersection so it is critical to view these spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Highway Division Safety Group
Name: Top 5% Intersection Crash Clusters 2017-2019
Display Field: Id
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top locations where reported collisions occurred at intersections have been identified. The crash cluster analysis methodology for the top intersection clusters uses a fixed meter search distance of 25 meters (82 ft.) to merge crash clusters together. This analysis was based on crashes where a police officer specified one of the following junction types: Four way intersection, T-intersection, Y-intersection, five point or more. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). The clustering analysis used crashes from the three year period from 2017-2019. The area encompassing the crash cluster may cover a larger area than just the intersection so it is critical to view these spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Office of Planning
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top locations where reported collisions occurred between bicyclists and motor vehicles have been identified. The crash cluster analysis methodology for the top bicyclist clusters uses a fixed meter search distance of 100 meters (328 ft.) to merge crash clusters together. Located crashes between motor vehicles and bicyclists were identified by using the non-motorist type code within the CDS database (which may yield different results from using most harmful event, first harmful event, or sequence of events data fields). Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. However, because of the relatively small number of reported bicyclists crashes in the crash data file, the clustering analysis used crashes from the ten year period from 2010-2019. Additionally, due to the larger geographic area encompassed by the bicyclist crash clusters, it was difficult to name them so they were left unnamed but can be viewed spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Office of Planning
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The top locations where reported collisions occurred between pedestrians and motor vehicles have been identified. The crash cluster analysis methodology for the top pedestrian clusters uses a fixed meter search distance of 100 meters (328 ft.) to merge crash clusters together. Located crashes between motor vehicles and pedestrians were identified by using the non-motorist type code as well as first harmful events and most harmful events within the CDS database. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). However, because of the relatively small number of reported pedestrian crashes in the crash data file, the clustering analysis used crashes from the ten year period from 2010-2019. Additionally, due to the larger geographic area encompassed by the pedestrian crash clusters, it was difficult to name them so they were left unnamed but can be viewed spatially.</SPAN></P></DIV></DIV></DIV>
Copyright Text: Massachusetts Department of Transportation Office of Planning