Injuries and fatalities for vulnerable road users, especially bicyclists and pedestrians, are on the rise. To better inform design for vulnerable road users, we need to evaluate how bicyclist and pedestrian behavior and physiological states change in different roadway design and contextual settings. Previous research highlights the advantages of using immersive virtual environments (IVEs) in conducting bicyclist and pedestrian studies. These environments do not put participants at risk of injury, are low cost compared to on-road or naturalistic studies, and allow researchers to fully control variables of interest. In this paper, we propose a framework, Omni-Reality and Cognition Lab Simulator (ORCLSim), to support human sensing techniques within IVEs to evaluate bicyclist and pedestrian physiological and behavioral changes in different contextual settings. To showcase this framework, we present two case studies, where pilot data from five participants’ physiological and behavioral responses in an IVE setting are collected and analyzed, representing real-world roadway segments and traffic conditions. Results from these case studies indicate that physiological data are sensitive to road environment changes and real-time events in the IVE, especially changes in heart rate and gaze behavior. In addition, our preliminary data indicate participants may respond differently to various roadway settings (e.g., signalized vs. unsignalized intersections). By analyzing these changes, future studies can identify how participants’ stress level and cognitive load are impacted by the surrounding environment. The ORCLSim system architecture is a prototype that can be customized for future studies in understanding users’ behavioral and physiological responses in virtual reality settings.
Recent reports indicate that cyclist fatalities are rising. Unlike automobile driver crash and safety studies, there is very limited information and data on how different environmental or design features impact cyclists’ behaviors, attention, and awareness. Real world studies evaluating cyclist behavior are limited due to their inherent safety risk; therefore, there is a need for alternate data to better inform the planning and design of roadways for all users. Immersive virtual environments (IVE) have shown to provide a realistic representation of real-world conditions; however, these tools have not been evaluated and validated for vulnerable road users, such as cyclists. The purpose of this study is to assess the use of an IVE bike simulator to study the impact of design and environmental conditions on cyclists’ perceived safety and behavioral changes. By benchmarking cyclists' behaviors and perceived safety in real-life settings compared to its representative IVE bike simulation, we can validate whether these IVE simulators are realistic representations of real-world conditions. Furthermore, by connecting these environments with the latest low-cost human sensing devices, we have built a multimodal human sensing data collection system to track participants’ gaze, heart rate, and head movement. The preliminary results from a six-participant pilot study indicate that our simulators are capable of replicating cyclists’ speed profile, heart rate changes, and most of the head and gaze behaviors and that these measurements are sensitive to environmental changes.
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