Naturalistic Driving Study: Technical Coordination and Quality Control (2014) / Chapter Skim
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1Executive Summary Introduction The Virginia Tech Transportation Institute (VTTI) served as the Coordination Contractor for the SHRP 2 Naturalistic Driving Study (NDS)
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2categories. Primary participants consented to have data collected from their main vehicle whenever it was driven during their participation in the study.
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Figure ES.2. DAS kit components (from upper left and moving clockwise: NextGen main unit, head unit, network box, RIB, and radar assembly)
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4NDS; additional quantities of several strategically chosen parts were purchased for logistical or replacement purposes. DAS sensors and capabilities included the following: • Multiple video and still views; • Machine-vision-based applications; • Accelerometers (x, y, and z axes)
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5Figure ES.6. Hands-on DAS installation training.
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6elevated crash risk. More than 18,000 individuals were recruited using a variety of approaches, and more than 3,000 ended up participating for 4 months or more.
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7participation in the study, regardless of the actual number of driving miles or hours represented during that time period. It is true to state, on the one hand, that driving distance and time are more accurate ways to determine overall data quantity, but these were also more difficult to accurately capture or estimate during the conduct of the study.
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8Sensor Data Once ingested into the database, data underwent a standardization process and a subsequent battery of automated quality checks as follows: • Not present indicates whether at least one data point was captured for a variable within a particular file. If a variable was not present for an entire file, no other checks for that variable were necessary.
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9• Complex dependency is similar to a simple dependency but with more complex conditions allowed. While a simple dependency was a function of the independent variable having "good" quality when the dependent variable was collected, a complex dependency could further refine what values of the independent variable indicated "good" quality for the dependent variable.
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10 Video data review of a sample of 10 trip files per month per participant was undertaken by a team of trained data reductionists under a protocol that elicited a quality assessment for each of the four camera views: face, forward, instrument panel, and rear. The quality assessment for each view was selected from one of four options, defined as follows: • Good quality: Video is clear, viewable, and correctly aligned.
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11 Participant-Related Outcomes Primary Participants by Age Figure ES.9 presents the total number of primary participants across age groups, with the horizontal line indicating the original study targets for each age group as per the original sample design. Vehicle-Related Outcomes Vehicles constituting the SHRP 2 fleet were further classified according to a number of parameters, including vehicle type and manufacturer.
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12 Manufacturer Figure ES.11 presents a view of the SHRP 2 vehicle fleet broken down by manufacturer. Crashes Five hundred thirty-two possible crash events were identified in the data set.
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13 frequency of occurrence diminishes. Thus far, more than 500 possible crashes have been identified, so the numbers in Figure ES.12 are expected to increase as the verification process continues.
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14 (including picture or video text messages) nor was the identity or number of the other person engaged in the call with the participant.
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15 Lessons Learned The SHRP 2 NDS has already led to a number of operational observations that should prove helpful to research teams undertaking similar ventures in the future, specifically in the areas of securing necessary human subjects protections, site-based facilitation, equipment management, and participant recruitment and management. Securing initial IRB approvals of study protocols and materials, and the approvals of subsequent amendments, took a great deal more time, money, and effort than was initially anticipated.
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