Evaluation of Data Needs, Crash Surrogates, and Analysis Methods to Address Lane

This report examines the statistical relationship between surrogate measures of collisions (conflicts, critical incidents, near collisions, or roadside encroachment) and actual collisions.

The primary objective of the work described in this report was to investigate the feasibility of using naturalistic driving study data to increase the understanding of lane departure crashes.

CONTENTS
Executive Summary
Identification of Lane Departure Research Questions and Necessary Factors
Identification of Data Necessary to Answer Research Questions
Methodological Approach to Selecting Lane Departure Crash Surrogates
Exploration of Analytical Approaches to Answer Lane Departure Research Questions
CHAPTER 1 Background
Introduction
Scope of Research
Organization of This Report
CHAPTER 2 Identifying Final Lane Departure Research Questions and Relevant Factors
Relevant Data Elements Identified in Existing Literature
Summarized List of Factors
Research Questions
CHAPTER 3 Data Sets Used
University of Michigan Transportation Research Institute Field Operational Test In-Vehicle Data
Michigan Geographic Framework and Sufficiency Report
Transportation Crash Master
Aerial Imagery
VTTI Naturalistic Driving Study from Data Request
VTTI Naturalistic Driving Study from the Internet
SHRP 2 Full-Scale Instrumented Vehicle Study
Summary of Terms Used to Describe Data
CHAPTER 4 Roadway, Driver, Environmental, and Vehicle Data Needs and Limitations to Address Lane Departures Using Naturalistic Driving Study Data
Background
Review of Roadway, Environmental, and Vehicle Data Elements Available in Existing Naturalistic Driving Study Data
Review of Planned Data Collection for Full In-Vehicle Naturalistic Driving Study
Review of Planned Data Elements from Mobile Mapping for Full-Scale Naturalistic Driving Study
Summary
Introduction
Background on Crash Surrogates
Summary of Crash Surrogates Used for Lane Departures
Selection of Lane Departure Surrogates
Evaluating Incident Outcome with UMTRI Data
Identifying Lane Departure Incidents Using Existing Data Sets
Determining Rollover Potential
Summary
CHAPTER 6 Analytical Tools and Initial Analysis of Lane Departure Research Questions
Objective
Audience
Data Availability in Full-Scale Naturalistic Driving Study to Answer Lane Departure Research Questions
Data Segmentation Approaches
General Information about Data Reduction
Analysis Approach 1: Data Mining
Analysis Approach 2: Odds Ratio and Logistic Regression
Analysis Approach 3: Logistic Regression for Correlated Data
Analysis Approach 4: Time Series Analysis
Summary and Conclusions
CHAPTER 7 Summary
References
Appendix A. Methodology for Extraction of Data Elements from the UMTRI Naturalistic Driving Study Data Set
Appendix B. Methodology for Extraction of Data Elements from the Virginia Tech Transportation Institute Naturalistic Driving Study Data Set
Appendix C. Assessment of Availability of Roadway Data Elements in the SHRP 2 Naturalistic Driving Study Data Acquisition System