I/UCRC Program Review XVII Driving Performance Data Verification Process at the NADS Judith Wightman Ginger S. Watson Judith Wightman Ginger S. Watson

I/UCRC Program Review XVII Data Verification at NADS Overview Raw Data Data Reduction Verification Tools Issues, Concerns, Future Research Overview Raw Data Data Reduction Verification Tools Issues, Concerns, Future Research

I/UCRC Program Review XVII Data Verification at NADS The goal is to ensure that collected data are –Reliable Consistent or reproducible –Valid Meaningful and relevant –Complete, yet concise The goal is to ensure that collected data are –Reliable Consistent or reproducible –Valid Meaningful and relevant –Complete, yet concise

I/UCRC Program Review XVII Raw Data Master list of up to 400 internal variables available on NADS Subset chosen based on goals of experiment –Binary collected in the data acquisition system (DAQ) –Various frequencies available per variable (up to 240 Hz) –Data can be converted to other formats and used in various ways MATLAB ASCII Excel ISAT (Interactive Scenario Authoring Tool; for playback) Reduced by coded algorithms Master list of up to 400 internal variables available on NADS Subset chosen based on goals of experiment –Binary collected in the data acquisition system (DAQ) –Various frequencies available per variable (up to 240 Hz) –Data can be converted to other formats and used in various ways MATLAB ASCII Excel ISAT (Interactive Scenario Authoring Tool; for playback) Reduced by coded algorithms

I/UCRC Program Review XVII Data Reduction The process of transforming raw data into meaningful summary variables (called “reduced data”) that address experimental hypotheses Components –Identifying and defining summary variables of interest –Filtering the data –Applying various algorithms (automated or human processed) to obtain the desired measures –Verifying that reduced data are valid (meaningful) and reliable (consistent) The process of transforming raw data into meaningful summary variables (called “reduced data”) that address experimental hypotheses Components –Identifying and defining summary variables of interest –Filtering the data –Applying various algorithms (automated or human processed) to obtain the desired measures –Verifying that reduced data are valid (meaningful) and reliable (consistent)

I/UCRC Program Review XVII Data Reduction Methods Automated code –Used to transform many data points into a concise measure such as reaction time –Examples Reaction time to 10% release in accelerator pedal from point of incurring vehicle creation Minimum time to collision with incurring vehicle from point of incurring vehicle creation Automated code –Used to transform many data points into a concise measure such as reaction time –Examples Reaction time to 10% release in accelerator pedal from point of incurring vehicle creation Minimum time to collision with incurring vehicle from point of incurring vehicle creation

I/UCRC Program Review XVII Data Reduction Methods Human coding –Used when video analysis or decomposition of non- driving behavior is needed, or when more efficient than automated coding –Examples Determination of number of seconds taken to dial a wireless phone Loss of control in ESC studies (90 degrees non- zero yaw rate) Human coding –Used when video analysis or decomposition of non- driving behavior is needed, or when more efficient than automated coding –Examples Determination of number of seconds taken to dial a wireless phone Loss of control in ESC studies (90 degrees non- zero yaw rate)

I/UCRC Program Review XVII Verification Tools ISAT –Displays top-down view of logical database and scenario saved in raw data stream –Allows for review of participant drives and examination of various reduced measures –Examples Verification of reaction time Verification of accelerator release ISAT –Displays top-down view of logical database and scenario saved in raw data stream –Allows for review of participant drives and examination of various reduced measures –Examples Verification of reaction time Verification of accelerator release

I/UCRC Program Review XVII Video Example

I/UCRC Program Review XVII ISAT Playback: Incurring Vehicle Creation

I/UCRC Program Review XVII ISAT Playback: Accelerator Release

I/UCRC Program Review XVII ISAT Playback: Brake Onset

I/UCRC Program Review XVII ISAT Playback: End of Event

I/UCRC Program Review XVII Verification Tools SAS/Excel –Used to calculate measures of central tendency for group or treatment, plot, or statistically analyze measures –Examples Velocity variance as calculated in SAS/Excel equivalent to the reduced variable velocity instability in certain situations Excel used for calculating length of various parameters of wireless call data (e.g., dial/answer, connect, converse, disconnect) SAS/Excel –Used to calculate measures of central tendency for group or treatment, plot, or statistically analyze measures –Examples Velocity variance as calculated in SAS/Excel equivalent to the reduced variable velocity instability in certain situations Excel used for calculating length of various parameters of wireless call data (e.g., dial/answer, connect, converse, disconnect)

I/UCRC Program Review XVII Verification Tools MATLAB –Used to plot performance over time –Example Sanity checks on phase (continuous measure of the delay in the participant’s reaction time to changes in lead vehicle’s speed) MATLAB –Used to plot performance over time –Example Sanity checks on phase (continuous measure of the delay in the participant’s reaction time to changes in lead vehicle’s speed)

I/UCRC Program Review XVII MATLAB Examples

I/UCRC Program Review XVII Issues, Concerns, Future Research Missing Data Generalizability Questions Missing Data Generalizability Questions