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GIS Display and Analysis of Crash Data Gautam Mistry University of Alabama, Tuscaloosa Prepared for: 29th International Traffic Records Forum July 15, 2003 Objectives – Mapping crashes stored in Critical Analysis Reporting Environment (CARE) on maps using GIS – Spatial Analysis of mapped crashes to identify patterns and hotspots CARE Critical Analysis Reporting Environment – Database maintained by the state of Alabama – Detailed information about vehicular crashes – Information can be retrieved by “data mining” – Crashes presented in tabular form and graphically in a linear form CARE Crashes can be selected meeting specific criteria Crash locations verbally described without coordinates State routes are graphically represented by a line and number of crashes represented as stack of points at mileposts shown as numbers Graphical display does not correlate with roadway features such as curves, bridges, rail-road crossings, and etc. CARE Location Data CARE stores crash locations in the form of nodes (intersection), links (roads), and route milepost (highways) – Crashes at intersections are identified by node numbers – Crashes on roads are identified by three fields: Link_ID, Node_1, Node_2 – Crashes on highways are identified by the route and milepost at which the crash occurred Creating Common Fields To connect the CARE data to the GIS roads layer, a common field is required to be created for nodes and links – Value of Node_1 is inserted in the column Connect_ID to represent crashes on intersections – The three fields describing links are concatenated to a single entity and placed under a separate column Connect_ID to represent crashes on links – A table containing crashes were directly added to the GIS file as an event table to represent the crashes in mileposted highways GIS Map Nodes layer was created, and node numbers were assigned for each intersection Link number (Link_ID) and node numbers (Node_1, Node_2) were manually inserted in the Roads layer for each road segment Routes were created for highways and milepost were assigned to the ends of the routes CARE Linked to GIS Node_ID column from nodes layer was related to Connect_ID column from CARE Connect_ID column in CARE database was related to Connect_ID column from roads layer in GIS for crashes that occurred on links Highway crashes are mapped on the routes created in GIS by dynamic segmentation BASE MAP Tuscaloosa County ® Spatial Analysis Hotspots are identified to indicate the locations with high crash frequencies using thematic mapping and buffering Thematic Map for Links ® Legend Number of Crashes on Links 0 1 2 3 ® Thematic Map for Nodes ") + $ Legend Crashes at Nodes 1-5 6 - 10 ") 11 - 15 + $ 16 - 20 ® Crashes on Links within 0.5-mile Buffer from Major Highways Legend 0.5-mile Buffer of Major Highways roads Number of Crashes 0 1 2 3 Spatial Analysis Crashes mapped on GIS can be spatially correlated to roadway features such as bridges, railroad crossings, crossroads, and etc. Thematic Map of Crashes at Rail-road Crossings !( !( + $ !( # * ® Legend !( roads rail Crashes at Railroad Crossings !( !( # * ") + $ 1 2 3 7 Crashes on Links near Rail-road Crossings Legend ® roads rail Number of Crashes on Links 0 1 4 Spatial Analysis Crashes on Interstate and State Highways were mapped according to the milepost at which the crashes occurred using dynamic segmentation Crashes on I-20/59 According to Milepost Tuscaloosa County !( ! !(!(( ! !( !(!(( !( !( !( !( !( !( !(!(!( !( !( !( !( !( (!!( !( (!!( !(!( !( !( !( !( !( !( !( (! !( !( (! (! !( !( !( !( !( !( !( ® !( (! !( Legend !( !( (!!( Crash Locations I - 20/59 county Conclusions This GIS application allows user to view the crashes on road map, which gives spatial representation of crashes It enables CARE data to be correlated with existing roadway features like bridges, rail-road crossings, and etc. It enables identification of hotspots and crash patterns at nodes, links, or route mileposts Use of multi-year data helps in graphical representation of before and after analysis Questions