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Keywords = truck-mounted attenuators

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21 pages, 5748 KiB  
Article
Automated Audible Truck-Mounted Attenuator Alerts: Vision System Development and Evaluation
by Neema Jakisa Owor, Yaw Adu-Gyamfi, Linlin Zhang and Carlos Sun
AI 2024, 5(4), 1816-1836; https://doi.org/10.3390/ai5040090 - 8 Oct 2024
Viewed by 1579
Abstract
Background: The rise in work zone crashes due to distracted and aggressive driving calls for improved safety measures. While Truck-Mounted Attenuators (TMAs) have helped reduce crash severity, the increasing number of crashes involving TMAs shows the need for improved warning systems. Methods: This [...] Read more.
Background: The rise in work zone crashes due to distracted and aggressive driving calls for improved safety measures. While Truck-Mounted Attenuators (TMAs) have helped reduce crash severity, the increasing number of crashes involving TMAs shows the need for improved warning systems. Methods: This study proposes an AI-enabled vision system to automatically alert drivers on collision courses with TMAs, addressing the limitations of manual alert systems. The system uses multi-task learning (MTL) to detect and classify vehicles, estimate distance zones (danger, warning, and safe), and perform lane and road segmentation. MTL improves efficiency and accuracy, making it ideal for devices with limited resources. Using a Generalized Efficient Layer Aggregation Network (GELAN) backbone, the system enhances stability and performance. Additionally, an alert module triggers alarms based on speed, acceleration, and time to collision. Results: The model achieves a recall of 90.5%, an mAP of 0.792 for vehicle detection, an mIOU of 0.948 for road segmentation, an accuracy of 81.5% for lane segmentation, and 83.8% accuracy for distance classification. Conclusions: The results show the system accurately detects vehicles, classifies distances, and provides real-time alerts, reducing TMA collision risks and enhancing work zone safety. Full article
(This article belongs to the Special Issue Artificial Intelligence-Based Image Processing and Computer Vision)
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16 pages, 3684 KiB  
Article
Noise Reduction and Localization Accuracy in a Mobile Magnetoencephalography System
by Timothy Bardouille, Vanessa Smith, Elias Vajda, Carson Drake Leslie and Niall Holmes
Sensors 2024, 24(11), 3503; https://doi.org/10.3390/s24113503 - 29 May 2024
Cited by 2 | Viewed by 1788
Abstract
Magnetoencephalography (MEG) non-invasively provides important information about human brain electrophysiology. The growing use of optically pumped magnetometers (OPM) for MEG, as opposed to fixed arrays of cryogenic sensors, has opened the door for innovation in system design and use cases. For example, cryogenic [...] Read more.
Magnetoencephalography (MEG) non-invasively provides important information about human brain electrophysiology. The growing use of optically pumped magnetometers (OPM) for MEG, as opposed to fixed arrays of cryogenic sensors, has opened the door for innovation in system design and use cases. For example, cryogenic MEG systems are housed in large, shielded rooms to provide sufficient space for the system dewar. Here, we investigate the performance of OPM recordings inside of a cylindrical shield with a 1 × 2 m2 footprint. The efficacy of shielding was measured in terms of field attenuation and isotropy, and the value of post hoc noise reduction algorithms was also investigated. Localization accuracy was quantified for 104 OPM sensors mounted on a fixed helmet array based on simulations and recordings from a bespoke current dipole phantom. Passive shielding attenuated the vector field magnitude to 50.0 nT at direct current (DC), to 16.7 pT/√Hz at power line, and to 71 fT/√Hz (median) in the 10–200 Hz range. Post hoc noise reduction provided an additional 5–15 dB attenuation. Substantial field isotropy remained in the volume encompassing the sensor array. The consistency of the isotropy over months suggests that a field nulling solution could be readily applied. A current dipole phantom generating source activity at an appropriate magnitude for the human brain generated field fluctuations on the order of 0.5–1 pT. Phantom signals were localized with 3 mm localization accuracy, and no significant bias in localization was observed, which is in line with performance for cryogenic and OPM MEG systems. This validation of the performance of a small footprint MEG system opens the door for lower-cost MEG installations in terms of raw materials and facility space, as well as mobile imaging systems (e.g., truck-based). Such implementations are relevant for global adoption of MEG outside of highly resourced research and clinical institutions. Full article
(This article belongs to the Special Issue Quantum Sensors and Their Biomedical Applications)
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28 pages, 1897 KiB  
Review
Countermeasures to Reduce Truck-Mounted Attenuator (TMA) Crashes: A State-of-the-Art Review
by Olugbemi Mosunmola Aroke, Ikechukwu Sylvester Onuchukwu, Behzad Esmaeili and Alejandra Medina Flintsch
Future Transp. 2022, 2(2), 425-452; https://doi.org/10.3390/futuretransp2020024 - 9 May 2022
Cited by 3 | Viewed by 5417
Abstract
To support worker and driver safety, this study conducted a comprehensive literature review to identify methods of enhancing TMA visibility, improving work zone configurations, and ensuring worker safety. To increase TMA recognition, this study observed that the use of a 6-to-8-inch wide yellow [...] Read more.
To support worker and driver safety, this study conducted a comprehensive literature review to identify methods of enhancing TMA visibility, improving work zone configurations, and ensuring worker safety. To increase TMA recognition, this study observed that the use of a 6-to-8-inch wide yellow and black inverted ‘V’ pattern of retroreflective chevron markings, sloped at a 45-degree angle downward in both directions from the upper center of a rear panel is effective in alerting drivers to work zones. This study also recommends applying amber and white warning LEDs, which flash in an asynchronous pattern at a 1 Hz frequency and are mounted against a solid-colored background for a 360-degree view visible at least 1500 feet from the work zone. In addition, a work zone vehicle configuration consisting of a lead, buffer, and advance warning truck with a buffer space between 100 and 150 ft is suggested to reduce the risk of lateral intrusions and TMA roll-ahead. In parallel, workers should wear high-visibility vests noticeable at a minimum distance of 1000 feet and headwear with at least 10 square inches of retroreflective material. Some intelligent transport systems are also suggested to enhance TMA recognition and potentially minimize work zone fatalities. Application of the recommended guidelines will potentially improve current practices and significantly reduce the occurrence of TMA crashes in construction and maintenance work zones. Full article
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