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Saving Lives with CARE New Developments: 2004 David B. Brown, PhD, PE brown@cs.ua.eduhttp://care.cs.ua.edu 30th International Traffic Records Forum Denver, Colorado July 27, 2004
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Background: Objective of CARE Maximum Safety Increases Fatality reduction Injury reduction Crash frequency reduction Severity reduction Within Budget Constraints
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Accomplishing This Objective Determine Extent of problem Potential for benefit Formulate Countermeasures Target - who, what, where Approach - when, why, how
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Reduction Potential Example Countermeasure: Hot Dots – Refectorized “stick- ons” given to young people in rural areas Sub-population children, age 5-16... involved in pedestrian crash... in the target areas (rural)... occurring in darkness. Potential: 3 Crashes per year (1.7% of problem) How many of these affected by Hot Dots? Could money better be spent on general program to help the 181 pedestrians injured age 5-16? The answer is obvious given the information.
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Advantages of Local Use Centralized Capability is Limited Locals Can Best Interpret Results Countermeasures Developed Must: Meet local needs Fit within local environment Fit available resources Local Use Improves Data Quality There is Nothing Like Hands-On
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CARE Objectives Provide Local/State Officials Complete analytical capability Minimal training On available equipment Public Domain: No software cost for CARE Web Updates accessible
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CARE Applications States Crash Databases 9 States with general system 2 States with locations (AL, GA) Other Database Types: Uniform Crime Reports – I/O, Arrest Drivers’ License, Juvenile, Citations Driver History, Convictions
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CARE Capabilities: General Easily define subsets (filters) For any subset and all variables: Frequency Cross-tabulation IMPACT: information mining High crash location analyses Collision diagrams – Intersection Magic Hotspot lists and reports
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What was the 2002 day-of-the- week distribution for crashes in Fulton Co, GA?
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Example Innovative Features User Interface: Filter Creation Filter creation from frequency or Xtab ANDs with the current filter Data Integration Roadway characteristics ADT Friction
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The Scenario Performing Alcohol Analysis Crosstab: Rural/Urban by Severity Identify problem in the rural areas Want to determine source of problem Solution Use CARE’s automated filter generation Perform Information Mining (IMPACT)
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Automated Filter Creation
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Following up with IMPACT
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Questions to be Addressed What role do the characteristics play in … Crash causation? Crash severity? Which characteristics are most important? Costs to change Potential for crash reduction Where should changes be made first? Provide benefit estimates Fit into resource optimization procedure Affect on roadway reconstruction?
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Roadway Characteristics and Crash Integration Goals: Integrate crash with road characteristics Obtain correlations: crashes & characteristics Identify potentially hazardous locations Provide crash reduction information
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Roadway Characteristics Integrated Number of Lanes (one/multiple) Average Grade Hill Crest/Sag (derived) Shoulder Surface Type and Condition Lane/Shoulder Width Outer/Inner Lane Superelevation Outer/inner Lane Width Curvature (derived) Proximal Curvature (derived) ADT (separate file) Friction (separate file)
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Major Accomplishments Summary Road Characteristics Written to crash data Nice for creating crash subsets Crashes Written to Roadway Data One Record Per 0.1 Mile in each direction All roadway characteristics in record Also: crashes for segments by severity
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New CARE Functionality Can Now Compare Crash with non-crash segments For all geometric & crash attributes Finding Problems … Before they cause crashes Directly from roadway characteristics
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To Illustrate Capabilities Example Direct Indicators of Hazards Friction Analyses Summary of worse roads High-crash location analysis Superelevation vs. Curvature CARE Runs 3501-5205 ADT 2L Crash vs. Non-Crash Lowest friction vs. higher frictions
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Superelevation vs. Curvature
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