Justin M. Owens

Creation of the Naturalistic Engagement in Secondary Tasks (NEST) distracted driving dataset

PROBLEM 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.

Reducing Conflict Between Vulnerable Road Users and Automated Vehicles

This chapter presents a summary of AVS 2016 Breakout Session 14, Reducing Conflict Between Vulnerable Road Users and Automated Vehicles. The session was scheduled to run for 90 min with approximately 60 min devoted to a panel of four speakers and 30 min of general discussion. The four speakers presented on a range of issues related to the intersection of VRUs and AVs. Key points included the need to develop usable, cross-cultural methods for pedestrians and AVs to communicate, the need to identify areas of opportunity and challenge relative to the current state of driver/VRU interactions, the need for further development and human factors testing of pedestrian-enabled mobile technology, and the importance of ongoing field testing.

Automated Vehicles (AVs) for People with Disabilities

This chapter presents insights from the AVS 2017 Breakout Session 24, AVs for People with Disabilities. The focus of this session was on creating awareness about the transportation needs and challenges that people with disabilities face. The emphasis was on how embracing universal design principles in developing AV technologies can make a significant difference in catering to all types of users equitably. Some of those design principles include enabling standards harmonization, data needs, and partnerships, as well as addressing policy barriers and technology challenges. The session was interactive with short thought-provoking presentations, and discussion questions. The discussions resulted in research topic recommendations for the United State Depart of Transportation’s (USDOT’s) Accessible Transportation Technologies Research Initiative (ATTRI) Program.

The Reality of Virtual Reality: A Comparison of Pedestrian Behavior in Real and Virtual Environments

Virtual reality (VR) can be a very effective tool to evaluate built environment to support improvement of pedestrian and other vulnerable road user safety. However, in order to draw actionable conclusions from VR it is important to understand the degree to which pedestrians’ perceptions and behaviors match across real and virtual environments. In this study, participants experienced equivalent real and virtual environments and performed similar tasks in each. Tasks included pedestrian’ intention to cross, estimation of speed and distance of an approaching vehicle, and the perceived safety and risk of crossing a road. Pedestrians’ presence was also measured in all environments. Result showed that there were no differences between the real and virtual environments for most of the tasks. Significant differences between real and virtual environments were observed in the estimation of speed and measures of presence. These results have important implications for using VR as tool to evaluate pedestrian safety in built environments.

Challenges and Opportunities for the Intersection of Vulnerable Road Users (VRU) and Automated Vehicles (AVs)

This chapter presents a summary of AVS 2017 Breakout Session 13, Challenges and Opportunities for the Intersection of Vulnerable Road Users (VRUs) and AVs. This session built upon a brief session in AVS 2016 devoted to reducing conflict between VRUs and automated vehicles [1]. As last year’s brief session resulted in significant engagement and discussion, this year’s session was expanded to a full afternoon to broaden the scope of presentation topics and discussion. Nine speakers presented on a range of issues related to the intersection of VRUs and AVs, ranging from lessons from the real world, to themes in human factors, to simulation and urban planning considerations. The session was organized around two main panel themes, focused on Vulnerable Road User Safety Needs and Concerns and Technology, Infrastructure and Policy Considerations. Significant discussion during and following the formal presentations resulted in identification of a range of research needs, including in the domains of AV design and human factors research, communications, legal and ethical questions, and data requirements.