01334334

Component

https://doi.org/10.3141/2237-01

http://scholar.google.com...gard&publication_year=2011

A preliminary study was done into the use and validation of crash surrogates, which are obtained from naturalistic driving studies for the detailed analysis of risk factors. The approach is based on a unified statistical analysis of crash data and surrogate events that uses a spatial referencing system and a common measure of exposure. Statistical methods based on a bivariate response and Bayesian update models were adapted to the joint analysis of crashes and surrogates. The study specifically addresses road-departure crashes involving a single vehicle. It is proposed that suitable surrogates be based on underlying continuous measures of disturbance in the driver’s lateral control of the vehicle. Naturalistic driving data from a field operational test conducted in southeastern Michigan were spatially joined with highway data and crash data from the same area, and a set of candidate crash surrogates was tested. Analysis results indicated that simple lateral lane position did not provide a satisfactory surrogate, whereas estimated time to road departure was found to show the correct statistical dependencies, consistent with the crash data. The approach developed in the study provided a way to assess crash risk in a common framework and also to validate or invalidate candidate surrogates. When applied to data from the future SHRP 2 naturalistic driving study, the increased statistical power resulting from the much larger data set will provide more definitive conclusions about surrogate validity and factors influencing overall crash risk.

01365008

11-1991

English

pp 1-9

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309222914

Print

Figures (3) ; References (15) ; Tables (1)

Crash data; Crash rates; Crash risk forecasting; Ran off road crashes; Single vehicle crashes; Statistical analysis

Surrogate safety measures

Michigan

Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics

TRIS, TRB

Feb 17 2011 6:00PM

• Accident Prediction Models for Winter Road Safety: Does Temporal Aggregation of Data Matter?
• Analysis of Speeding Behavior: Multilevel Modeling Approach
• Data-Mining Techniques for Exploratory Analysis of Pedestrian Crashes
• Effect of Arterial Signal Coordination on Safety
• Estimation of Real-Time Crash Risk: Are All Freeways Created Equal?
• Fully Bayesian Approach to Investigate and Evaluate Ranking Criteria for Black Spot Identification
• High-Resolution Detector and Signal Data to Support Crash Identification and Reconstruction
• Identifying Crash Distributions and Prone Locations by Lane Groups at Freeway Diverging Areas
• Improved Time-to-Collision Definition for Simulating Traffic Conflicts on Truck-Only Infrastructure
• Methodologies for Aggregating Indicators of Traffic Conflict
• Mining Microscopic Data of Vehicle Conflicts and Collisions to Investigate Collision Factors
• Modeling Highway Safety and Simulation in Rainy Weather
• Performance of Safety Indicators in Identification of Black Spots on Two-Lane Rural Roads
• Random Parameter Model Used to Explain Effects of Built-Environment Characteristics on Pedestrian Crash Frequency
• Surrogate Safety Measures for Optimizing Investments in Local Rural Road Networks
• U.S. National Household Travel Survey Used to Validate Exposure Estimates by the Quasi-Induced Exposure Technique