Dataset Information

Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior.

ABSTRACT: The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior. We examined whether there is a specific discrete time point for each driver, in the form of total driving duration and/or the number of trips, beyond which the characteristics of driving behavior are stabilized over time. Various mathematical and statistical methods were employed to process the data collected and determine the time point at which behavior converges. Detailed data collected from smartphone sensors are used to test the proposed methodology. The driving metrics used in the analysis are the number of harsh acceleration and braking events, the duration of mobile usage while driving and the percentage of time driving over the speed limits. Convergence was tested in terms of both the magnitude and volatility of each metric for different trips and analysis is performed for several trip durations. Results indicated that there is no specific time point or number of trips after which driving behavior stabilizes for all drivers and/or all metrics examined. The driving behavior stabilization is mostly affected by the duration of the trips examined and the aggressiveness of the driver.

SUBMITTER: Stavrakaki AM

PROVIDER: S-EPMC7248787 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior.

Stavrakaki Anna-Maria AM Tselentis Dimitrios I DI Barmpounakis Emmanouil E Vlahogianni Eleni I EI Yannis George G

Sensors (Basel, Switzerland) 20200502 9

The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior. We examined whether there is a specific discrete time point for each driver, in the form of total driving duration and/or the number of trips, beyond which the characteristics of driving behavior are stabilized over time. Various mathematical and statistical methods were employed to ...[more]

PMID: 32370264

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Project description:ObjectiveThere is a substantial body of evidence that the recidivism of impaired-driving offenders is reduced while an ignition interlock device (IID) is on their vehicles. This study examines changes in driving behaviors and drinking behaviors used by DWI offenders to manage driving with the IID.MethodsA total of 166 IID participants who completed two surveys covering the period from arrest to IID installation (T1) and during IID use (T2) were examined. Four domains were covered: demographics, driving environments and transportation needs, reported driving activity, and reported drinking activities. Participants were on average 38 years old, 43% were female, 35% completed college, 34% had an income of more than $50,000, and 83% were employed. For those who provided it, the mean blood alcohol content (BAC) at arrest was .184 g/dL, with only 8 (5%) individuals below .08 g/dL, and 93 (56%) at over .18 g/dL. About 45% were repeat DWI offenders.ResultsBetween T1 and T2 there was a slight increase in acknowledging public transportation was available (p=.001), an increase in other individuals driving the interlock-equipped vehicle (p=.002), an increase in the number of vehicles in the household not registered to the DWI offender (p< .001), and an increase in the number of participants who reported that driving was important to their lifestyle (p=.008). Initial (T1) expectations about whether the interlock would be a problem were significantly different from actual experiences reported in T2 (p<.001). With respect to alcohol consumption, 14% reported abstinence at T2 compared to 2% at T1 (p=.001) and the number of drinks per drinking occasion decreased from a mean of 4.90 at T1 to 3.14 at T2 (p=.001), but the number of drinking occasions increased by a third (p=.003). The number of drinking locations (p=.001), the frequency of stopping after work for a drink (p=.001), and drinking at a bar all decreased (p<.001).ConclusionsInterlock users make some adjustments in how they drink, the amount they drink, and where they drink. This finding suggests that there may be methods that can be used to extend the benefits of the IID beyond the sanction period.

Project description:Background: The number of older adults in the United States will double by 2056. Additionally, the number of licensed drivers will increase along with extended driving-life expectancy. Motor vehicle crashes are a leading cause of injury and death in older adults. Alzheimer's disease (AD) also negatively impacts driving ability and increases crash risk. Conventional methods to evaluate driving ability are limited in predicting decline among older adults. Innovations in GPS hardware and software can monitor driving behavior in the actual environments people drive in. Commercial off-the-shelf (COTS) devices are affordable, easy to install and capture large volumes of data in real-time. However, adapting these methodologies for research can be challenging. This study sought to adapt a COTS device and determine an interval that produced accurate data on the actual route driven for use in future studies involving older adults with and without AD. Methods: Three subjects drove a single course in different vehicles at different intervals (30, 60 and 120 seconds), at different times of day, morning (9:00-11:59AM), afternoon (2:00-5:00PM) and night (7:00-10pm). The nine datasets were examined to determine the optimal collection interval. Results: Compared to the 120-second and 60-second intervals, the 30-second interval was optimal in capturing the actual route driven along with the lowest number of incorrect paths and affordability weighing considerations for data storage and curation. Discussion: Use of COTS devices offers minimal installation efforts, unobtrusive monitoring and discreet data extraction. However, these devices require strict protocols and controlled testing for adoption into research paradigms. After reliability and validity testing, these devices may provide valuable insight into daily driving behaviors and intraindividual change over time for populations of older adults with and without AD. Data can be aggregated over time to look at changes or adverse events and ascertain if decline in performance is occurring.

Dataset Information

Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior.

Publications

Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior.

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