Crash Modification Factor Development: Data Needs and

Protocols

Raghavan Srinivasan

Daniel CarterUNC 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

http://www.cmfclearinghouse.org/

http://safety.fhwa.dot.gov/tools/crf/resources/fhwasa10032/

http://safety.fhwa.dot.gov/tools/crf/resources/cmfs/

CMFs in Practice

http://www.cmfclearinghouse.org/collateral/CMF_Protocols.pdf

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