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Browsing by Author "Valente, Jacob T."

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    Creating a Dataset of Naturalistic Ambulance Driving: A Pilot Study of Two Ambulances
    Valente, Jacob T.; Terranova, Paolo; Perez, Miguel A. (National Surface Transportation Safety Center for Excellence, 2024-08-02)
    Motor vehicle collisions (MVCs) are an everyday occurrence in the United States. This pressing transportation and health care topic affects millions of citizens each year, and in many cases may result in fatality or lifelong injury complications. Despite best efforts, and notable success, to improve the frequency and severity of MVCs, these events are still a prevalent issue. In the wake of an MVC, crash occupants rely on emergency responders to quickly respond to the scene, control hazards, and administer necessary medical care. Efficiency within the emergency response event, to an MVC or some other medical care need, is contingent on a properly working transportation system, allowing emergency medical services (EMS) to travel to and from scenes both quickly and safely. Previous research has revealed that complex interactions with other road users not only hinders emergency response efficiency, but often results in hazardous and dangerous interactions on roadways. To capture these complex interactions from a firsthand perspective, this report details a naturalistic driving study that involved two ambulances and the subsequent dataset that was generated, which is the first of its kind. A custom data acquisition system was used to collect four external and three internal video perspectives on each vehicle, with continuous vehicle data that included vehicle speed, GPS location, and emergency system activation (i.e., emergency light or siren use). Following data collection, the dataset was summarized in the context of each participating agency, the consented drivers, trip type (emergent vs. non-emergent), trip duration, trip distance, and the time of day that the trip took place. The dataset was also processed through a map-matching algorithm that utilized the collected GPS data to provide additional context, including posted speed limit road classification. Finally, the dataset was subsampled to assess and interpret other road user behavior during emergent trips. The work outlined in this report serves as the foundation for additional research that could be leveraged from this dataset, as this dataset is intended to support the inquiry of future research questions within the scope of emergency vehicle operation and transportation. Additionally, some findings of this study and their implications apply beyond the scope of emergency MVC response and may be related more broadly to emergency response for all first responders and emergency events.
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    Emergency Response to Vehicle Collisions: Feedback from Emergency Medical Service Providers
    Valente, Jacob T.; Perez, Miguel A. (MDPI, 2020-10-20)
    (1) Background: The purpose of this study is to identify emergency medical technicians’ perceptions of the most pressing issues that they experience when responding to motor vehicle collisions and record their opinions about what information is needed to improve the efficiency and effectiveness of the care they provide. (2) Methods: Emergency medical technicians participated in one-on-one structured interviews about their experiences responding to motor vehicle collisions. Their feedback on dispatching procedures and protocols, travel to and from the scene, and the response process was collected. (3) Results: Participants reported experiencing difficulties related to lack of or inaccuracies in information, interactions with traffic, incompatibility in communication technology, scene safety, resource management, and obtaining timely notifications of motor vehicle collisions. Regarding the type of information most needed to improve emergency medical response, respondents indicated a desire for additional data related to the vehicle and its occupants. (4) Conclusions: The early and widespread availability of this information is expected to aid emergency responders in coordinating necessary resources faster and more optimally, help service optimization in situations with multiple motor vehicle collisions in close temporal proximity, and improve on-scene safety for first responders and other necessary personnel.