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Driver Attitudes and Behaviors

at Intersections and Potential

Effectiveness of Engineering

Countermeasures

PUBLICATION NO. FHWA-HRT-05-078

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FOREWORD

This report describes the results of a focus group study that explored driver attitudes and behaviors at intersections to assess the likely impacts of new or existing infrastructure-based technologies/countermeasures. The focus group study is part of a larger research project that will provide the Federal Highway Administration (FHWA) with information about roadway user attitudes and behaviors at intersections. Specifically, the information concerns driving performance, perceptual and cognitive bottlenecks, constraints that can negatively impact intersection safety, and engineering or educational countermeasures for intersection safety with the greatest likely impact on performance and safety.

Michael F. Trentacoste,
Director,
Office of Safety Research and Development


Notice

This document is disseminated under the sponsorship of the Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document. This report does not constitute a standard, specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trade and manufacturers’ names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

Technical Report Documentation Page
1. Report No 
FHWA–HRT–05–078		2. Government Accession No.3. Recipient’s Catalog No.
4. Title and Subtitle 
Driver Attitudes and Behaviors at Intersections and
Potential Effectiveness of Engineering Countermeasures		5. Report Date 
November 2005
6. Performing Organization Code
 N/A
7. Authors(s) 
Richard, C. M., Michaels, E. F., and Campbell, J. L.		8. Performing Organization Report No.
9. Performing Organization Name and Address 
Battelle Human Factors Transportation Center
1100 Dexter Avenue North
Seattle, WA 98109-3598		10. Work Unit No. (TRAIS)
 N/A
11. Contract or Grant No. 
DTFH61-04-00006
12. Sponsoring Agency Name and Address 
Office of Safety Research and Development
Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296
13. Type of Report and Period Covered 
Focus Group Study, May 24, 2004–March 3, 2005
14. Sponsoring Agency Code
 N/A
15. Supplementary Notes 
Contracting Officer’s Technical Representative (COTR): Ray Krammes
Task Manager: Thomas M. Granda
16. Abstract 

The objective of this focus group study was to identify driver attitudes and behaviors related to intersection safety and to assess the likely impacts of new or existing infrastructure-based technologies/countermeasures. Four focus groups were conducted at each of three test sites: Washington, DC; Chicago, IL; and Seattle, WA. At each site, the four groups corresponded to the age/gender characteristics identified as important to this project. The four groups were:
  • 18- to 35-year-old female drivers only.
  • 18- to 35-year-old male drivers only.
  • 35- to 55-year-old drivers of both genders.
  • 65+-year-old drivers of both genders.
At each site, the focus groups took place over two separate evenings, with two focus groups conducted per evening. A total of 119 individuals participated in the focus groups. The effort focused on identifying driver attitudes and behaviors with respect to four intersection scenarios: (1) red-light running, (2) left turns at busy intersections, (3) turning left onto a major road with moderate traffic, and (4) rear-end crashes. For each of these four scenarios, results and conclusions relevant to the following key questions are developed and presented:
  • What are drivers most likely to do in this scenario?
  • Why do drivers engage in these behaviors?
  • What engineering countermeasures have the most promise for improving traffic safety?
17. Key Words 
Driver attitudes and behaviors, focus groups,
intersection safety, engineering countermeasures		18. Distribution Statement 
No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161.
19. Security Classif. (of this report) 
Unclassified 		20. Security Classif. (of this page) 
Unclassified 		21. No. of Pages 
174		22. Price 
Form DOT F 1700.7 (8–72)Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

TABLE OF CONTENTS

CHAPTER 1. INTRODUCTION

CHAPTER 2. METHODS FOR CONDUCTING THE FOCUS GROUPS

     OVERVIEW
          Selection of Focus Group Discussion Scenarios
     SELECTING THE TEST SITES
     REFINING RECRUITMENT SCREENERS, MODERATOR GUIDES, AND FOCUS GROUP MATERIALS
          Participant Screener
          Moderator Guides
          Other Materials (Countermeasures)
          Take–Home Survey
     IDENTIFYING, SCREENING, AND SCHEDULING RESPONDENTS
          Participant Sources/Pools
          Scheduling Respondents
     ORGANIZING AND SCHEDULING FOCUS GROUP FACILITIES, INCLUDING AUDIOVISUAL CAPABILITIES
     CONDUCTING THE FOCUS GROUPS
     ANALYZING AND SUMMARIZING THE HIGHLIGHTS OF THE FOCUS GROUP DISCUSSIONS

CHAPTER 3. RESULTS

     INTRODUCTION
     PARTICIPANT RESPONSES TO THE FOUR DRIVING SCENARIOS
          Scenario 1: Red-Light Running
          Scenario 2: Left Turns at Busy Intersections
          Scenario 3: Turning Left onto a Major Road with Moderate Traffic
          Scenario 4: Rear-End Crashes
     PARTICIPANT RESPONSES TO THE NINE ENGINEERING COUNTERMEASURES
          Countermeasure 1.1: Red-Light Camera
          Countermeasure 1.2: High-Visibility Traffic Lights
          Countermeasure 1.3: Advance Traffic-Light Warning Signs
          Countermeasure 1.4: Intersection Collision-Warning Systems
          Countermeasure 2.1: Protected Left-Turn Lights
          Countermeasure 3.1: Automatic Gap Detection
          Countermeasure 3.2: Synchronized Adjacent Traffic Signals
          Countermeasure 4.1: Intersection Rumble Strips
          Countermeasure 4.2: Improved Skid Resistance
     TAKE-HOME SURVEY RESULTS
          Introduction
          Survey Results
     CORRELATIONS AMONG ELEMENTS OF THE INTEGRATED BEHAVIORAL MODEL (IBM)

CHAPTER 4. CONCLUSIONS

     SCENARIO 1: RED-LIGHT RUNNING
          What are drivers most likely to do in this scenario?
          Why do drivers engage in these behaviors?
          What engineering countermeasures have the most promise for improving traffic safety?
     SCENARIO 2: LEFT TURNS AT BUSY INTERSECTIONS
          What are drivers most likely to do in this scenario?
          Why do drivers engage in these behaviors?
          What engineering countermeasures have the most promise for improving traffic safety?
     SCENARIO 3: TURNING LEFT ONTO A MAJOR ROAD WITH MODERATE TRAFFIC
          What are drivers most likely to do in this scenario?
          Why do drivers engage in these behaviors?
          What engineering countermeasures have the most promise for improving traffic safety?
     SCENARIO 4: REAR-END CRASHES
          What are drivers most likely to do in this scenario?
          Why do drivers engage in these behaviors?
          What engineering countermeasures have the most promise for improving traffic safety?
     FUTURE RESEARCH DIRECTIONS
          Red-Light Running
          Left Turns at Intersections
          Left Turns at Stop–Controlled Intersections
          Rear–End Crashes
          Application of This Methodology to Other Scenarios or Safety Issues

APPENDIX A. PARTICIPANT SCREENER

APPENDIX B. MODERATOR’S GUIDE

APPENDIX C. TAKE-HOME SURVEY

APPENDIX D. TABULAR SUMMARY OF THE FOCUS GROUP RESULTS

REFERENCES


LIST OF FIGURES

Figure 1. Flow of research inputs, activities, and deliverables
Figure 2. Graphic 1 used to describe scenario 1: Red-light running
Figure 3. Graphic 2 used to describe scenario 1: Red-light running
Figure 4. Graphic 1 used to describe scenario 2: Left turns at busy intersections
Figure 5. Graphic 2 used to describe scenario 2: Left turns at busy intersections
Figure 6. Graphic used to describe scenario 3: Turning left onto a major road with moderate traffic
Figure 7. Graphic 1 used to describe scenario 4: Rear-end crashes
Figure 8. Graphic 2 used to describe scenario 4: Rear-end crashes
Figure 9. Graphics and text used to describe countermeasure 1.1: Red-light camera
Figure 10. Graphics and text used to describe countermeasure 1.2: High-visibility traffic lights
Figure 11. Graphics and text used to describe countermeasure 1.3: Advance traffic–light warning signs
Figure 12. Graphics and text used to describe countermeasure 1.4: Intersection collision–warning systems
Figure 13. Graphics and text used to describe countermeasure 2.1: Protected left-turn lights
Figure 14. Graphics and text used to describe countermeasure 3.1: Automatic gap detection
Figure 15. Graphics and text used to describe countermeasure 3.2: Synchronized adjacent traffic signals
Figure 16. Graphics and text used to describe countermeasure 4.1: Intersection rumble strips
Figure 17. Graphics and text used to describe countermeasure 4.2: Improved skid resistance
Figure 18. The integrated behavioral model (IBM)
Figure 19. Summary of key scale responses pooled across gender, age, and location
Figure 20. Responses to question 1 as a function of driver age
Figure 21. Responses to question 2 as a function of driver age
Figure 22. Responses to question 3 as a function of driver age
Figure 23. Responses to question 4 as a function of driver age
Figure 24. Responses to question 12a as a function of driver age
Figure 25. Responses to question 12b as a function of driver age
Figure 26. Responses to combined questions 8 and 9 as a function of driver age
Figure 27. Responses to combined question 10 as a function of driver age
Figure 28. Responses to combined question 6 as a function of driver age


LIST OF TABLES

Table 1. Relative frequency of intersection crossing-path crashes.(1)
Table 2. Focus group discussion scenarios
Table 3. Scenario countermeasures for the focus groups
Table 4. Number of focus group participants as a function of location and age/gender characteristics
Table 5. Number of take-home surveys returned from each participant group as a function of location, and age/gender characteristics
Table 6. Results from question 5: "Can you think of any other benefits or negative results of going through an intersection on a late yellow/early red light?"
Table 7. Results from question 11: "If you said that it is not under your control in the previous question, what makes you go through the intersection on a late yellow light?"
Table 8. Results from question 7: "Have you been involved in a traffic crash at an ntersection in the last year, 5 years, ever, or never?"
Table 9. Correlations and p-values (italicized) between reported intersection behaviors and intentions, and the factors that influence them
Table 10. Correlations and p-values (italicized) between reported intersection behaviors and intentions, and gender/age characteristics of the focus group participants
Table 11. Research questions, candidate research approaches, and benefits from focus group results
Table 12. Syntax for Group and Strength columns
Table 13. What are drivers most likely to do in this situation (scenario 1)?
Table 14. What factors influence driver decisions to stop (scenario 1)?
Table 15. What factors influence driver decisions to go through (scenario 1)?
Table 16. What are some additional external factors that influence driver decisions (scenario 1)?
Table 17. Do drivers anticipate and plan a response for a dilemma–zone situation as they approach an intersection, or do they react on the fly to the yellow light and the corresponding driving conditions (scenario 1)?
Table 18. What other information do drivers use when making decisions regarding going through or stopping (scenario 1)?
Table 19. Is going through the light ever a deliberate act (scenario 1)?
Table 20. Is it ever the case that drivers do not notice the signal until it is too late to do anything but continue through the red? Do drivers ever try to stop in this case (scenario 1)?
Table 21. Complicating factors (scenario 1)
Table 22. What are driver attitudes regarding red-light running (scenario 1)?
Table 23. What do drivers believe are the consequences of running red lights (scenario 1)?
Table 24. Do drivers’ beliefs about the consequences come into play in their decision process (scenario 1)?
Table 25. How does experience with critical events (e.g., crashes, near-misses) impact their decisions, attitudes, beliefs, etc. (scenario 1)?
Table 26. To what extent is red-light running behavior impacted by perceived social norms (scenario 1)?
Table 27. To what extent is the act of going through the light under their control (scenario 1)?
Table 28. To what degree, if any, does habit (e.g., "I don’t think about it, I just always do it that way") affect whether or not drivers run a red light (scenario 1)?
Table 29. What are drivers most likely to do in this situation (scenario 2)?
Table 30. What steps do drivers take in making the turns (scenario 2)?
Table 31. How do drivers decide (what steps are involved) whether or not a gap in traffic is sufficient (scenario 2)?
Table 32. What other information or considerations come into play (scenario 2)?
Table 33. What are some of the strategies that drivers use in this situation (scenario 2)?
Table 34. Complicating factors (scenario 2)
Table 35. What are drivers most likely to do in this situation (scenario 3)?
Table 36. What steps do drivers take in completing the action (scenario 3)?
Table 37. What is the decisionmaking process (scenario 3)?
Table 38. How do drivers decide (what steps are involved) whether or not a gap in traffic is sufficient? What factors are relevant (e.g., speeds, distance to cross, weather) (scenario 3)?
Table 39. What size gaps are drivers comfortable with (scenario 3)?
Table 40. What external factors make the task of deciding when to turn more complicated/difficult or more demanding (scenario 3)?
Table 41. Complicating factors (scenario 3)
Table 42. How many drivers have been involved as the following vehicle in a rear-end crash or had a near-miss at an intersection (scenario 4)?
Table 43. What were the circumstances that caused the incident to happen (scenario 4)?
Table 44. How closely do respondents typically follow other vehicles? What factors determine how closely drivers follow other vehicles (scenario 4)?
Table 45. What are some strategies for avoiding rear-end conflict situations (scenario 4)?
Table 46. How do drivers detect or anticipate when the lead vehicle will slow or stop (scenario 4)?
Table 47. What are drivers likely to do in response to this situation (scenario 4)?
Table 48. Complicating factors (scenario 4)
Table 49. Would implementing this countermeasure improve safety (countermeasure 1.1)?
Table 50. What are some of the implementation issues (countermeasure 1.1)?
Table 51. What are some of the advantages and disadvantages (countermeasure 1.1)?
Table 52. What would it take to make red-light cameras acceptable (countermeasure 1.1)?
Table 53. Would implementing this countermeasure improve safety (countermeasure 1.2)?
Table 54. What are some of the implementation issues (countermeasure 1.2)?
Table 55. What are some of the advantages and disadvantages (countermeasure 1.2)?
Table 56. Would implementing this countermeasure improve safety (countermeasure 1.3)?
Table 57. What are some of the implementation issues (countermeasure 1.3)?
Table 58. Advantages and disadvantages (countermeasure 1.3)
Table 59. Would implementing this countermeasure improve safety (countermeasure 1.4)?
Table 60. What are some of the implementation issues (countermeasure 1.4)?
Table 61. Advantages and disadvantages (countermeasure 1.4)
Table 62. How does this system compare to an in-vehicle warning system (countermeasure 1.4)?
Table 63. Would implementing this countermeasure improve safety (countermeasure 2.1)?
Table 64. What are some of the implementation issues (countermeasure 2.1)?
Table 65. Would implementing this countermeasure improve safety (countermeasure 3.1)?
Table 66. What are some of the implementation issues (countermeasure 3.1)?
Table 67. What are some of the advantages and disadvantages (countermeasure 3.1)?
Table 68. Gap advisory system (countermeasure 3.1)
Table 69. Would implementing this countermeasure improve safety (countermeasure 3.2)?
Table 70. What are some of the implementation issues (countermeasure 3.2)?
Table 71. What are some of the advantages and disadvantages (countermeasure 3.2)?
Table 72. Would implementing this countermeasure improve safety (countermeasure 4.1)?
Table 73. What are some of the implementation issues (countermeasure 4.1)?
Table 74. What are some of the advantages and disadvantages (countermeasure 4.1)?
Table 75. Would implementing this countermeasure improve safety (countermeasure 4.2)?
Table 76. What are some of the implementation issues (countermeasure 4.2)?
Table 77. What are some of the advantages and disadvantages (countermeasure 4.2)?

 


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