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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- Analysis of Driver Behavioral Adaptation to the Lateral Drift Warning SystemGreenstein, A. (2014-08-27)
- Assessment of Psychophysiological Characteristics of Drivers Using Heart Rate from SHRP2 Face Video DataSarkar, 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
- Automated Drive Analysis of Naturalistic Driving Studies with Looking-out VideoGunaratne, Pujitha; Martin, Sujitha; Ohn-Bar, Eshed; Satzoda, Ravi; Trivedi, Mohan (2014-08-25)
- Can cab engineering create passive improvements in driver sleep, health, and fuel efficiency?Loczi, J.; Olson, Rebecca Lynn (2014-08-25)
- Canadian Naturalistic Driving StudyHankey, Jonathan M. (2014-08-25)
- A Complex Driving Scenario for Describing Safety-Critical Event CausationDunn, Naomi J.; Hickman, Jeffrey S.; Hanowski, Richard J. (2014-08-25)
- Constructing a Distracted Driving DatasetFoley, 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.
- Crowd-sourced Connected-vehicle Warning Algorithm using Naturalistic Driving DataNoble, Alexandria M.; McLaughlin, Shane B.; Doerzaph, Zachary R.; Dingus, Thomas A. (2014-08-25)
- Data and IRB issues in International Naturalistic Driving StudyLee, Suzanne E. (2014-08-25)Cultural expectations vary among regions; there are different expectations of privacy, volunteering criteria, and duties as a citizen. These differences such as driving laws may very well augment the risks that participants face. That being, if someone is considering being a human subject, he or she should become familiar with current laws/policies regarding human subjects. He or she should also learn about the collaborators and their familiarity with human subjects. Lastly, consent documents should be recognized as explicit with regard to international aspects specifically stating who will have access to the compiled data.
- Data Mining for Driver Behavior in Normal DrivingGuyonvarc'h, Laurette; Josseaume, Francoise; Chauvel, Cyril; Guillaume, Anne; Lutz, Michael (2014-08-25)Driving behavior
- Drivers' Visual Behavior When Using Hand-Held and Hands-Free Cell PhonesFitch, Gregory M.; Guo, Feng; Hanowski, Richard J.; Perez, M. P. (2014-08-25)This study investigated driver distraction and how the use of handheld (HH), portable hands-free (PHF), and integrated hands-free (IHF) cell phones affected the visual behavior of motor vehicle drivers. Method A naturalistic driving study recorded 204 participating drivers using video cameras and vehicle sensors for an average of 31 days. A total of 1564 cell phone calls made and 844 text messages sent while driving were sampled and underwent a video review. Baselines were established by recording epochs prior to the cell phone interactions. Total eyes-off-road time (TEORT) was examined to assess the visual demands of cell phone subtasks while driving. Percent TEORT was reported and compared against the baseline. Results Visual-manual subtasks performed on HH, PHF, and IHF cell phones were found to significantly increase drivers' mean percent TEORT. In contrast, conversing on an HH cell phone was found to significantly decrease drivers' mean percent TEORT, indicating that drivers looked at the forward roadway more often. No significant differences in percent TEORT were found for drivers conversing using PHF or IHF cell phones. The mean TEORT durations for visual-manual subtasks performed on an HH cell phone were significantly longer than the mean TEORT durations on either IHF or PHF cell phones. Practical applications This research helps to further reinforce the distinction made between handheld and hands-free cell phone use in transportation distraction policy.
- Evaluating the Sleeper-Berth Provision: Preliminary Investigation into Usage Characteristics and Safety-Critical Event InvolvementSoccolich, Susan A.; Blanco, Myra; Hanowski, Richard J. (2014-08-25)
- Evaluation of feedback to truck drivers to increase safe driving behaviors: Preliminary findingsBell, Jennifer L.; Wirth, Oliver; Taylor, Matt; Chen, Guang-Xiang; Kirk, Rachel (2014-08-25)
- Examination of drivers' cell phone use behavior at intersections by using naturalistic driving dataXiong, 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.
- Examining the Relationship between Drug Use and Involvement in a Safety-Critical EventCamden, Matthew C.; Soccolich, Susan A.; Hickman, Jeffrey S.; Hanowski, Richard J. (2014-08-25)
- Extending Naturalistic Driving Research to a Patrol Car: A Pilot ProjectGarrison, Teena M.; Carruth, Daniel W. (2014-08-25)
- LiDAR: Another Potential Data SourceHarwood, Leslie C.; Doerzaph, Zachary R. (2014-08-25)LiDAR (Light Detection and Ranging) is a valuable tool for evaluating line of sight. Though setup is time-intensive, it can to be used as an automated process. It is more objective and efficient than video reduction or survey methods.
- Naturalistic Assessment of the First 10 Hours of Driving: The Supervised PracticeEhsani, Johnathon P.; Simons-Morton, Bruce G.; Klauer, Charlie; Lee, Suzanne E.; Guo, Feng; Dingus, Thomas A. (2014-08-25)