Crash Modification Factor Development: Data Needs and Protocols Raghavan Srinivasan Daniel Carter UNC Highway Safety Research Center

Background Science of highway safety advancing Data-driven decisions Crash modification factors (CMFs) used more widely –Countermeasure selection –Benefit-cost analysis Resources for CMFs expanding

CMFs in Practice

CMF Protocols Need protocols for CMFs –Consistent –Clear in their application –Statistically rigorous –Free of biases –High rating in the CMF Clearinghouse –Acceptable for future editions of the HSM

Audience Researchers –Addressing potential biases –Documenting work Research sponsors –Writing problem statements –Evaluating contractor work

Scope Crash-based Infrastructure-related countermeasures (signs, signals, markings, barriers, etc)

Background Work Literature review across many study methods Web survey and phone interviews with CMF researchers

How Prescriptive? Protocols could be very prescriptive Specify study methodology (e.g., empirical Bayes) –May not be appropriate –May not be possible –May oppress use of more innovative methods Specify statistical confidence level –Depends on sample size and data variability –Funding, time period of data, availability of sites

What is the Intent? If not prescriptive, then what? What is the intent? –Consistent –Clear in their application –Statistically rigorous –Free of biases –Acceptable for HSM and high rating in the CMF Clearinghouse Need to know how CMF was developed Need to know how potential biases were addressed

Documentation General documentation (for determining applicability) Biases documentation (for determining quality)

General Documentation CMF and Countermeasure –Detailed countermeasure description: “Install 3- strand high-tension cable median barrier” –Prior condition: “Depressed grass median without barrier” –The Crash Modification Factor or Crash Modification Function –Measure of precision of the CMF

General Documentation Site characteristics –Roadway type: 4 to 6 lane freeway –Geographic area: Rural –Traffic volume range: 20,000 to 40,000 AADT –Other site characteristics

General Documentation Crash characteristics –Type: Cross-median crashes –Severity: Fatal and injury crashes –Other crash characteristics

General Documentation Study details –Sample size: 210 miles –Years: 6 years (3 before, 3 after) –Selection criteria: High incidence of target crashes –Other study details

Biases Documentation Cross-sectional studies Before-after studies Issues that affect all studies

Potential Cross-Sectional Biases Confounders Heterogeneity / omitted variable State-to-state differences Appropriate functional form Correlation or collinearity Overfitting Small sample mean and size Aggregation, averaging, or incompleteness in data Temporal and spatial correlation Endogenous independent variables Misspecification of structure of systematic variation and residual terms Correlation between crash types and injury severities

Potential Before-After Biases Regression-to-the-mean Changes in traffic volumes Trends Changes in crash reporting State-to-state differences if using multiple states Suitability of comparison or reference groups Other biases for before-after studies

Issues That Affect All Studies Data quality (abrupt increases/decreases, suspicious trends) –Crashes –AADT Crash type and severity Crash modification factor vs. function

Overall Objective Better CMF Documentation Better Knowledge of CMF Applicability Better Knowledge of CMF Quality Better CMF Studies