Combining Crash and Enforcement Location Data to Determine Selective Enforcement Strategies 4 th Annual GIS Symposium - Troy November 16, 2007.

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Presentation transcript:

Combining Crash and Enforcement Location Data to Determine Selective Enforcement Strategies 4 th Annual GIS Symposium - Troy November 16, 2007

Outline Data sources Starting point Mapping crashes (points, lines, regions) ECitation Mapping citations (points, lines, regions) Hot and cold zones Process summary Future plans Bonus material

Data Sources Crashes –Paper crash reports (ECrash) –Mapable by route & milepost –Three month lag on most crashes –Complete Alabama data for past 15 years Citations –ECitation –GPS –Two to three day lag on most citations –State trooper and some municipalities (Oldest data 2002) Officer Locations –Real-time for some troopers –Plan to recorded positions periodically

Starting Point The questions –When & where should officers patrol to reduce fatalities and serious injuries? –How is “the answer” best presented? –How should recommendation effectiveness be assessed? Conventional wisdom: –Position enforcement operations in high crash locations (“hotspots”)

Crash Points 4 years of mileposted crashes

Crashes Per Trooper Post

Five-mile segments Reflect overall activity within a particular segment A coarser-grained look at activity than simply displaying individual crashes Segments Instead of Points

Crashes as Graduated Lines

Other Ways to Slice Look at subsets of crashes: –Fatalities –Injuries –Alcohol –Etc. Overlay other types of data: –Traffic volume –Roadway characteristics –Enforcement patterns

Electronic Citations in Alabama Initiated in June 2002 Approximately 420,000 transactions to date: –360,000 citations –60,000 warnings –1700 transactions per day Deployment –Most state troopers (around 450 officers) –91 officers at 10 local agencies –46 agencies in progress Real-time citation GPS locations

Citation Points GPS

Citations Per Post

Citations as Graduated Lines

Hot & Cold Zone Designation Crashes Citations Above AverageBelow Average Above Average NACold Zone Below Average Hot ZoneNA

Computing Hot/Cold Zones Based on trooper post Hot zone - 5-mile segments where: –Crashes exceed the post average for crashes –Citations are below the post average for citations Cold zone - 5-mile segments where: –Citations exceed the post average for citations –Crashes are below the post average for crashes A possible officer deployment strategy: –Route officers to hot zones –Route officers away from cold zones, except where they overlap hot zones

Above and Below Post-Average-Crashes Per 5 Mile Segment Mobile Post

Above and Below Post-Average-Citations Per 5 Mile Segment Mobile Post

Hot & Cold Zones  Hot Zones  Below Average Citations  Above Average Crashes  Cold Zones  Above Average Citations  Below Average Crashes

Process Summary

Next Step Need to implement enforcement decisions based on this strategy Need to monitor the effectiveness of shifting resources: –Does reducing citations negatively impact a low-crash coldspot? –Does increasing citations positively impact a high-crash hotspot? Based on the results of this evaluation, continue to shift resources Ultimately: –Make enforcement decisions based on data, not feel

Future Plans Data quality and timeliness: –Obtain 85-90% of citation data electronically (with GPS coordinates) –Obtain real-time crash data with GPS coordinates using ECrash Incorporate officer location data –Analyze crashes and citations and officer patrol locations Identify routes, not just locations Develop more sophisticated algorithm for identifying hot & cold zones

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