Publications by authors named "Zachary D Asher"

The accurate identification of medicine vials is crucial for emergency medical services, especially for vials that resemble one another but have different labels, volumes, and concentrations. This study introduces a method to detect vials in real-time using mixed reality technology through Microsoft HoloLens 2. The system is also equipped with an SQL server to manage barcode and vial information.

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Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources.

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External human-machine interfaces (eHMIs) serve as communication bridges between autonomous vehicles (AVs) and road users, ensuring that vehicles convey information clearly to those around them. While their potential has been explored in one-to-one contexts, the effectiveness of eHMIs in complex, real-world scenarios with multiple pedestrians remains relatively unexplored. Addressing this gap, our study provides an in-depth evaluation of how various eHMI displays affect pedestrian behavior.

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Safe autonomous vehicle (AV) operations depend on an accurate perception of the driving environment, which necessitates the use of a variety of sensors. Computational algorithms must then process all of this sensor data, which typically results in a high on-vehicle computational load. For example, existing lane markings are designed for human drivers, can fade over time, and can be contradictory in construction zones, which require specialized sensing and computational processing in an AV.

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Article Synopsis
  • The automotive industry is rapidly advancing in the commercialization of autonomous vehicle (AV) technology, but there's a lack of accessible literature on developing AV research platforms.
  • A methodology and results are presented involving the instrumentation and controls of a 2019 Kia Niro optimized for AV research, featuring various advanced sensors and software systems.
  • The total cost for the developed platform is $118,189 USD with a power consumption of 242.8 Watts, showcasing significant savings compared to other commercial systems, and it serves as a key research tool for ongoing AV development.
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