4th International Symposium on Naturalistic Driving Research

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The National Surface Transportation Safety Center for Excellence (NSTSCE) at Virginia Tech Transportation Institute hosted the Fourth International Symposium on Naturalistic Driving Research at The Inn at Virginia Tech and Skelton Conference Center in Blacksburg, Virginia from August 25-28th, 2014. The two-day international symposium (preceded and followed by full-day workshops on Monday, August 25th and Thursday, August 28th) gathered experts in the field of naturalistic driving research to discuss a wide range of topics.

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  • Why Conducting In-Depth Naturalistic Riding Study?... Examples from Rider Trainees and Novices in France
    Espié, Stéphane; Aupetit, Samuel; Delgehier, Flavien; Bouaziz, Samir (2014-08-27)
  • Examining the Relationship between Drug Use and Involvement in a Safety-Critical Event
    Camden, Matthew C.; Soccolich, Susan A.; Hickman, Jeffrey S.; Hanowski, Richard J. (2014-08-25)
  • Personality and Crash Risk
    Ehsani, Johnathon P.; Simons-Morton, Bruce G.; Li, Kaigang; Perlus, Jessamyn G.; O'Brien, Fearghal (2014-08-25)
    Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Method: Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18 months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate, and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants' KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Results: Conscientiousness was marginally negatively associated with CNC (path c = − 0.034, p = .09) and both potential mediators KRD (path a = − 0.040, p = .09) and secondary task engagement while driving (path a = − 0.053, p = .03). KRD, but not secondary task engagement, was found to mediate (path b = 0.376, p = .02) the relationship between conscientiousness and CNC (path c′ = − 0.025, p = .20). Conclusions: Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, and suffered fewer CNC. Practical Applications: Part of the variability in crash risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers' personality into account when providing guidance, and establishing norms and expectations about driving.
  • Teenage Driver Cellular Phone Use During the First Months of Driving
    Creaser, Janet (2014-08-25)
    Distracted driving is a significant concern for novice teen drivers. Although cellular phone bans are applied in many jurisdictions to restrict cellular phone use, teen drivers often report making calls and texts while driving. Method The Minnesota Teen Driver Study incorporated cellular phone blocking functions via a software application for 182 novice teen drivers in two treatment conditions. The first condition included 92 teens who ran a driver support application on a smartphone that also blocked phone usage. The second condition included 90 teens who ran the same application with phone blocking but which also reported back to parents about monitored risky behaviors (e.g., speeding). A third control group consisting of 92 novice teen drivers had the application and phone-based software installed on the phones to record cellular phone (but not block it) use while driving. Results The two treatment groups made significantly fewer calls and texts per mile driven compared to the control group. The control group data also demonstrated a higher propensity to text while driving rather than making calls. Discussion Software that blocks cellular phone use (except 911) while driving can be effective at mitigating calling and texting for novice teen drivers. However, subjective data indicates that some teens were motivated to find ways around the software, as well as to use another teen's phone while driving when they were unable to use theirs. Practical applications Cellular phone bans for calling and texting are the first step to changing behaviors associated with texting and driving, particularly among novice teen drivers. Blocking software has the additional potential to reduce impulsive calling and texting while driving among novice teen drivers who might logically know the risks, but for whom it is difficult to ignore calling or texting while driving.
  • A Complex Driving Scenario for Describing Safety-Critical Event Causation
    Dunn, Naomi J.; Hickman, Jeffrey S.; Hanowski, Richard J. (2014-08-25)
  • Naturalistic Assessment of the First 10 Hours of Driving: The Supervised Practice
    Ehsani, Johnathon P.; Simons-Morton, Bruce G.; Klauer, Charlie; Lee, Suzanne E.; Guo, Feng; Dingus, Thomas A. (2014-08-25)
  • Using Naturalistic Driving Data to Examine Age and Gender Differences on Seat Belt Use
    Bao, Shan; Xiong, Huimin; Sayer, James; Buonarosa, Mary Lynn (2014-08-25)
    Teens and young drivers are often reported as one driver group that has significantly lower seatbelt use rates than other age groups. Objective This study was designed to address the questions of whether and how seatbelt-use behavior of novice teen drivers is different from young adult drivers and other adult drivers when driving on real roads. Method Driving data from 148 drivers who participated in two previous naturalistic driving studies were further analyzed. The combined dataset represents 313,500 miles, 37,695 valid trips, and about 9500 h of driving. Drivers did not wear their seatbelts at all during 1284 trips. Two dependent variables were calculated, whether and when drivers used seatbelts during a trip, and analyzed using logistic regression models. Results Results of this study found significant differences in the likelihood of seatbelt use between novice teen drivers and each of the three adult groups. Novice teen drivers who recently received their driver's licenses were the most likely to use a seatbelt, followed by older drivers, middle-aged drivers, and young drivers. Young drivers were the least likely to use a seatbelt. Older drivers were also more likely to use seatbelts than the other two adult groups. The results also showed that novice teen drivers were more likely to fasten their seatbelts at the beginning of a trip when compared to the other three adult groups. Summary Novice teen drivers who were still in the first year after obtaining their driver's license were the most conservative seatbelt users, when compared to adult drivers. Practical application Findings from this study have practical application insights in both developing training programs for novice teen drivers and designing seatbelt reminder and interlock systems to promote seatbelt use in certain driver groups.
  • An Overview of Methods and Key Findings from the NTDS: The Naturalistic Teenage Driving Study: Methods and Selected Findings
    Simons-Morton, Bruce G.; Klauer, Charlie; Guo, Feng; Lee, Suzanne E.; Ouimet, Marie-Claude; Albert, Paul S.; Dingus, Thomas A. (2014-08-25)
    This paper summarizes the findings on novice teenage driving outcomes (e.g., crashes and risky driving behaviors) from the Naturalistic Teenage Driving Study. Method Survey and driving data from a data acquisition system (global positioning system, accelerometers, cameras) were collected from 42 newly licensed teenage drivers and their parents during the first 18 months of teenage licensure; stress responsivity was also measured in teenagers. Result Overall teenage crash and near-crash (CNC) rates declined over time, but were > 4 times higher among teenagers than adults. Contributing factors to teenage CNC rates included secondary task engagement (e.g., distraction), kinematic risky driving, low stress responsivity, and risky social norms. Conclusions The data support the contention that the high novice teenage CNC risk is due both to inexperience and risky driving behavior, particularly kinematic risky driving and secondary task engagement. Practical Applications Graduated driver licensing policy and other prevention efforts should focus on kinematic risky driving, secondary task engagement, and risky social norms.
  • Examination of drivers' cell phone use behavior at intersections by using naturalistic driving data
    Xiong, Huimin; Bao, Shan; Kato, Kazuma; Sayer, James (2014-08-25)
    Many driving simulator studies have shown that cell phone use while driving greatly degraded driving performance. In terms of safety analysis, many factors including drivers, vehicles, and driving situations need to be considered. Controlled or simulated studies cannot always account for the full effects of these factors, especially situational factors such as road condition, traffic density, and weather and lighting conditions. Naturalistic driving by its nature provides a natural and realistic way to examine drivers' behaviors and associated factors for cell phone use while driving. Method In this study, driving speed while using a cell phone (conversation or visual/manual tasks) was compared to two baselines (baseline 1: normal driving condition, which only excludes driving while using a cell phone, baseline 2: driving-only condition, which excludes all types of secondary tasks) when traversing an intersection. Results The outcomes showed that drivers drove slower when using a cell for both conversation and visual/manual (VM) tasks compared to baseline conditions. With regard to cell phone conversations, drivers were more likely to drive faster during the day time compared to night time driving and drive slower under moderate traffic compared to under sparse traffic situations. With regard to VM tasks, there was a significant interaction between traffic and cell phone use conditions. The maximum speed with VM tasks was significantly lower than that with baseline conditions under sparse traffic conditions. In contrast, the maximum speed with VM tasks was slightly higher than that with baseline driving under dense traffic situations. Practical applications This suggests that drivers might self-regulate their behavior based on the driving situations and demand for secondary tasks, which could provide insights on driver distraction guidelines. With the rapid development of in-vehicle technology, the findings in this research could lead the improvement of human-machine interface (HMI) design as well.
  • Weighted Feature Extraction for Driving Maneuver Recognition: A Study using Naturalistic UTDrive Data
    Zheng, Yang; Sathyanarayana, Amardeep; Hansen, John H. L. (2014-08-25)
  • Time Series Analysis of Driver Behavior on Curves
    Wang, Bo; Hallmark, Shauna; Oneyear, Nicole (2014-08-25)
    Over half of motor vehicle fatalities are roadway departures, with rural horizontal curves being of particular interest because they make up only a small share of the system mileage but have a crash rate that is significantly higher than tangent sections. However the interaction between the driver and roadway environment is not well understood, and, as a result, it is difficult to select appropriate countermeasures. Method In order to address this knowledge gap, data from the SHRP 2 naturalistic driving study were used to develop relationships between driver, roadway, and environmental characteristics and risk of a road departure on rural curves. The SHRP 2 NDS collected data from over 3,000 male and female volunteer passenger vehicle drivers, ages 16–98, during a three year period, with most drivers participating between one to two years. A Roadway Information Database was collected in parallel and contains detailed roadway data collected on more than 12,500 centerline miles of highways in and around the study sites. Results Roadway data were reduced for rural 2-lane curves and included factors such as geometry, shoulder type, presence of rumble strips, etc. Environmental and traffic characteristics, such as time of day, ambient conditions, or whether the subject vehicle was following another vehicle, were reduced from the forward roadway video view. Driver characteristics, such as glance location and distraction were reduced from the driver and over the shoulder videos. Conclusions Logistic regression models were developed to assess the probability (odds) of a given type of encroachment based on driver, roadway, and environmental characteristics. At the point this study was undertaken, crashes and near crashes were not yet available and only around 1/3 of the full SHRP NDS dataset could be queried. As a result, the likelihood of crossing the right or left lane line (encroachments) and speeding were used as dependent variables.
  • Crowd-sourced Connected-vehicle Warning Algorithm using Naturalistic Driving Data
    Noble, Alexandria M.; McLaughlin, Shane B.; Doerzaph, Zachary R.; Dingus, Thomas A. (2014-08-25)
  • Predictors of Crash Risk for Novice Drivers
    Ehsani, Johnathon P. (2014-08-25)
  • Assessment of Psychophysiological Characteristics of Drivers Using Heart Rate from SHRP2 Face Video Data
    Sarkar, Abhijit; Doerzaph, Zachary R.; Abbott, A. Lynn (2014-08-25)
    The goal is to
    • Extract heart rate from face video
    • Understand the behavior of driver, e.g. cognitive load, panic attack, drowsiness, DUI
    • Develop automatic video reduction technique
    • Devise a tool for future
  • Evaluation of feedback to truck drivers to increase safe driving behaviors: Preliminary findings
    Bell, Jennifer L.; Wirth, Oliver; Taylor, Matt; Chen, Guang-Xiang; Kirk, Rachel (2014-08-25)
  • Constructing a Distracted Driving Dataset
    Foley, James; Ebe, Kazu; Owens, Justin M.; Angell, Linda; Hankey, Jonathan M. (2014-08-25)
    Distracted driving has become a topic of critical importance to driving safety research over the past several decades. Naturalistic driving data offer a unique opportunity to study how drivers engage with secondary tasks in real-world driving; however, the complexities involved with identifying and coding relevant epochs of naturalistic data have limited its accessibility to the general research community. Method This project was developed to help address this problem by creating an accessible dataset of driver behavior and situational factors observed during distraction-related safety-critical events and baseline driving epochs, using the Strategic Highway Research Program 2 (SHRP2) naturalistic dataset. The new NEST (Naturalistic Engagement in Secondary Tasks) dataset was created using crashes and near-crashes from the SHRP2 dataset that were identified as including secondary task engagement as a potential contributing factor. Data coding included frame-by-frame video analysis of secondary task and hands-on-wheel activity, as well as summary event information. In addition, information about each secondary task engagement within the trip prior to the crash/near-crash was coded at a higher level. Data were also coded for four baseline epochs and trips per safety-critical event. Results 1,180 events and baseline epochs were coded, and a dataset was constructed. The project team is currently working to determine the most useful way to allow broad public access to the dataset. Discussion We anticipate that the NEST dataset will be extraordinarily useful in allowing qualified researchers access to timely, real-world data concerning how drivers interact with secondary tasks during safety-critical events and baseline driving. Practical applications The coded dataset developed for this project will allow future researchers to have access to detailed data on driver secondary task engagement in the real world. It will be useful for standalone research, as well as for integration with additional SHRP2 data to enable the conduct of more complex research.