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Publication Number: FHWA-HRT-14-077
Date: July 2014

 

The Exploratory Advanced Research Program Fact Sheet

Utilizing Various Data Sources for Surface Transportation Human Factors Research

WORKSHOP SUMMARY REPORT   •   November 6-7, 2013

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Technical Report Documentation Page

1. Report No.

FHWA-HRT-14-077

2. Government Accession No. 3 Recipient's Catalog No.
4. Title and Subtitle

Utilizing Various Data Sources for Surface Transportation Human Factors Research
Workshop Summary Report · November 6–7, 2013

5. Report Date

July 2014

6. Performing Organization Code
7. Author(s)

Alicia Romo, Bianka Mejia, and C.Y. David Yang

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

VOLPE National Transportation Center
55 Broadway
Cambridge, MA 02142

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

N/A

12. Sponsoring Agency Name and Address

Office of Operations Research and Development and Office of
Corporate Research, Technology, and Innovation Management
Federal Highway Administration
6300 Georgetown Pike
McLean, Virginia 22101

13. Type of Report and Period Covered

Workshop Summary Report, November 2013

14. Sponsoring Agency Code

 

15. Supplementary Notes

FHWA's Contracting Officer's Task Manager (COTM): Zachary Ellis, HRTM-30
Technical Contact: David Yang

16. Abstract

This report summarizes a 2-day workshop held on November 6-7, 2013, to discuss data sources for surface transportation human factors research. The workshop was designed to assess the increasing number of different datasets and multiple ways of collecting data that can be used to increase understanding of human errors. Participants discussed how to resolve the controversies among different datasets and how to choose the best datasets for particular applications. Expert speakers shared their research experience of using various datasets from sources such as driving simulators, field studies and field operational tests, and naturalistic driving studies. The expert panel identified several potential research topics to address the challenges that must be overcome to integrate data from multiple sources.

17. Key Words

Surface transportation, human factors research, data sources, human errors, datasets, data integration, driving simulators, field studies, field operational tests, naturalistic driving studies.

18. Distribution Statement

No restriction. This document is available to the public through the National Technical Information Service, Springfield, VA 22161.

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

68

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

 

SI* (Modern Metric) Conversion Factors

EXECUTIVE SUMMARY

On November 6–7, 2013, at the Turner–Fairbank Highway Research Center in McLean, VA, the Federal Highway Administration’s (FHWA) Office of Safety Research and Development, with support from the Exploratory Advanced Research (EAR) Program, convened the workshop, ”Utilizing Various Data Sources for Surface Transportation Human Factors Research.” The workshop addressed the increasing number of different datasets and multiple ways of collecting data—from naturalistic driving and simulator studies to eye trackers and surveys—that can be used to increase an understanding of human errors.

Human errors are still a major cause of injuries and fatalities; however, a number of different datasets have recently become available to analyze human errors. These datasets point in different directions within different areas of interaction. Experts in human factors research, transportation safety, and driver behavior and performance analysis, met to discuss and determine which datasets were best and how one might resolve the differences. The information provided by the different datasets is sometimes complementary, sometimes competing, and sometimes confirmatory.  The workshop brought together a panel of experts to share their research experience of using multiple methods to gain insights about different aspects of driver and traveler behavior and performance. 

During day one of this workshop, participants heard seven presentations on using various datasets from sources such as driving simulators, field studies and field operational tests, and naturalistic driving studies. The experts discussed various methods to study behaviors that lead to errors and shared strategies they have deployed to gain insightful information about what datasets to use to target one or more human factors or behavior issues. The workshop also presented the idea of using multiple data collection methods to “cross-reference” analysis results, validate conclusions, and enhance the understanding of behaviors.

On day two of the workshop, an expert panel discussed issues related to consolidating data from multiple types of collection methods. The experts discussed how datasets must be carefully examined when combined from different sources. For example, some data sources are contradictory, leaving researchers with the need to conduct additional research to resolve the controversies. Alternatively, other data sources can be complementary and provide information in the field and in the laboratory on driver behaviors that point in a similar direction. How best to create complementary datasets also needs to be carefully considered. In addition, very few data sources are comprehensive, and they do not provide information on both driver behavior and crashes. The ability to develop models that can link behavioral datasets with crash datasets, leading to comprehensive datasets, is still in its infancy. The expert panel went on to identify several potential research topics to address the challenges that must be overcome to integrate data from multiple sources.

At the end of day two, the workshop sponsor divided the participants into three groups so that detailed discussion could be held to identify research gaps related to the following interactions of drivers: (1) with other road users, (2) with changing elements of the roadway and infrastructure, and (3) with their own vehicle. All three groups presented summaries of their discussion and recommendations to conclude this workshop.

Workshop panelists and participants noted two different ways of seeing how best to deal with multiple contradictory datasets, as follows:

Panelists were unanimous in recommending that there should be an attempt to understand how to use the different types of data in a study that includes the following components:

As part of the final workshop recommendations, participants identified many areas of priority for human factors research that could make use of the expanding datasets now available and soon to be available. These included modeling, safety, roadway departure, urban intersections, vehicle, pedestrian and bicyclist interaction, and data analysis. Participants suggested a number of specific items for further research, as follows:

To further understanding and use of multiple data types, participants recommended a study, possibly focused at intersections, which includes multiple sites, multiple data types gathered at each site, multiple user types, and multiple methods of analysis. This study could provide critical information on how to resolve contradictions among datasets, how to put together complementary datasets that describe risky behaviors, and how to generate comprehensive datasets that link behaviors and crashes.

Table of Contents

Introduction

Day One: Presentations

Day Two: Discussion and Summary

Appendices

List of Figures


List of Acronyms and Abbreviations

General Terms
ACCadaptive cruise control
ASV-3Advanced Safety Vehicle-3
CICAS-SSAcooperative intersection collision avoidance system–stop sign assist
DOTDepartment of Transportation
DSRCdedicated short-range communications
EARExploratory Advanced Research
FHWAFederal Highway Administration
FOTfield operational test
GPSGlobal Positioning System
HAWKHigh-intensity Activated crossWalK
IEEEInstitute of Electrical and Electronics Engineers
IMUinertial measurement units
ITSIntelligent Transportation System
IV-DSRCinter-vehicle dedicated short-range communications
LIDARlight detection and ranging
MUTCDManual on Uniform Traffic Control Devices
NADSNational Advanced Driving Simulator
NHTSANational Highway Traffic Safety Administration
NSFNational Science Foundation
OTLobserved time lag
PIprincipal investigator
PTLpredicted time lag
PV-DSRCpedestrian–vehicle dedicated short-range communications
SHRP 2second Strategic Highway Research Program
STRADASwedish Traffic Accident Data Acquisition
TCDtraffic control devices
TMCtraffic management center
TxDOTTexas Department of Transportation
UMTRIUniversity of Michigan Transportation Research Institute
USDOTU.S. Department of Transportation
V2Vvehicle-to-vehicle
VehDAQvehicle data acquisition
VOQvehicle operator questionnaire
WTIWestern Transportation Institute

Introduction

Transportation safety is the top priority at the Federal Highway Administration (FHWA) and U.S. Department of Transportation (USDOT). A high percentage of transportation incidents and vehicle crashes are caused by human errors. As a result, it is important to continue investing in research resources to gain a comprehensive understanding of human errors and to try to answer the question, “Why do drivers and travelers do what they do?”

The motivation for this workshop was in large part a function of the increasing number of different datasets and multiple ways of collecting data—from naturalistic driving and simulator studies to eye trackers and surveys—that can be used to increase our understanding of human errors. Now is an ideal time to begin a discussion about how to resolve the differences and how to choose the best datasets for particular applications.

To initiate this discussion, FHWA's Office of Safety Research and Development, with support from the Exploratory Advanced Research (EAR) Program, convened the workshop, “Utilizing Various Data Sources for Surface Transportation Human Factors Research,” on November 6–7, 2013. Experts in transportation safety analysis and driver behavior and performance, were invited to the Turner–Fairbank Highway Research Center in McLean, VA, to share their research experience of using multiple methods to gain insights into different aspects of driver and traveler behavior and performance.

A primary question posed to researchers was how best to select the particular datasets most helpful for analyzing one of the following three major research topics: (1) the interaction between drivers and other road users, such as pedestrians and bicyclists; (2) the interaction between drivers and roadway and other transportation infrastructure; and (3) the interaction between drivers and their vehicles. This report captures highlights from the workshop and summarizes the discussions that took place.

 

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