Vehicles with driving automation are increasingly being developed for deployment across the world. However, the onboard sensing and perception capabilities of such automated or autonomous vehicles (AV) may not be sufficient to ensure safety under all scenarios and contexts. Infrastructure-augmented environment perception using roadside infrastructure sensors can be considered as an effective solution, at least for selected regions of interest such as urban road intersections or curved roads that present occlusions to the AV. However, they incur significant costs for procurement, installation and maintenance. Therefore these sensors must be placed strategically and optimally to yield maximum benefits in terms of the overall safety of road users. In this paper, we propose a novel methodology towards obtaining an optimal placement of V2X (Vehicle-to-everything) infrastructure sensors, which is particularly attractive to urban AV deployments, with various considerations including costs, coverage and redundancy. We combine the latest advances made in raycasting and linear optimization literature to deliver a tool for urban city planners, traffic analysis and AV deployment operators. Through experimental evaluation in representative environments, we prove the benefits and practicality of our approach.
In this paper, we introduce the notion of Cooperative Perception Error Models (coPEMs) towards achieving an effective and efficient integration of V2X solutions within a virtual test environment. We focus our analysis on the occlusion problem in the (onboard) perception of Autonomous Vehicles (AV), which can manifest as misdetection errors on the occluded objects. Cooperative perception (CP) solutions based on Vehicle-to-Everything (V2X) communications aim to avoid such issues by cooperatively leveraging additional points of view for the world around the AV. This approach usually requires many sensors, mainly cameras and LiDARs, to be deployed simultaneously in the environment either as part of the road infrastructure or on other traffic vehicles. However, implementing a large number of sensor models in a virtual simulation pipeline is often prohibitively computationally expensive. Therefore, in this paper, we rely on extending Perception Error Models (PEMs) to efficiently implement such cooperative perception solutions along with the errors and uncertainties associated with them. We demonstrate the approach by comparing the safety achievable by an AV challenged with a traffic scenario where occlusion is the primary cause of a potential collision.
The worldwide development of Autonomous Vehicles (AVs) has also encouraged the use of software simulators for virtual testing of AVs. However, the effectiveness of the AV simulators is constrained by numerous challenges, such as their computational cost and lack of fidelity in specific areas. In this paper, we describe the modality of virtual testing and its benefits for AV development and validation. Moreover, we summarize and provide an overview of the state-of-the-art AV simulators, their limitations, and the current directions toward improvement.
Vehicles with driving automation are increasingly being developed for deployment across the world. However, the onboard sensing and perception capabilities of such automated or autonomous vehicles (AV) may not be sufficient to ensure safety under all scenarios and contexts. Infrastructure-augmented environment perception using roadside infrastructure sensors can be considered as an effective solution, at least for selected regions of interest such as urban road intersections or curved roads that present occlusions to the AV. However, they incur significant costs for procurement, installation and maintenance. Therefore these sensors must be placed strategically and optimally to yield maximum benefits in terms of the overall safety of road users. In this paper, we propose a novel methodology towards obtaining an optimal placement of V2X (Vehicle-to-everything) infrastructure sensors, which is particularly attractive to urban AV deployments, with various considerations including costs, coverage and redundancy. We combine the latest advances made in raycasting and linear optimization literature to deliver a tool for urban city planners, traffic analysis and AV deployment operators. Through experimental evaluation in representative environments, we prove the benefits and practicality of our approach.
Introduction: Instrument separation is one of the most stressful endodontic mishaps, that can occur any time during the root canal treatment. Several techniques have been employed to facilitate instrument retrieval, however, most of them are technique sensitive, expensive and require great expertise. It is possible to successfully remove broken file from the root canal using sonic agitation coupled with H-files with minimal damage to radicular dentin, if the file separation is in the straight and visible part of the canal. Case Report: A 29-year-old man reported to the Department of Conservative Dentistry and Endodontics, with a chief complaint of pain in the upper front teeth for which the patient had undergone previous dental treatment, but with no relief in pain. The patient gave a history of treatment in the same tooth at a private clinic 3 months back. Conclusion: The technique used in this case report might be considered a conservative, secure, simple and low-cost option that can be performed by any professional in the day-to-day of the endodontic clinic.
Introduction: Non-carious lesions are caused as a result of tooth surface loss. Several categories of tooth surface loss exist, including erosion, attrition, abrasion and abfraction. Numerous factors, such as bruxism, clenching, disease, dietary considerations, lifestyle choices, improper tooth brushing, abrasive dentrifices, craniofacial complex, iatrogenic dentistry and ageing might contribute to this problem. It can be challenging to identify the cause, but it is feasible by observing the pattern of tooth surface loss on the teeth, and it is essential for treatment planning to avoid failure. Prevention, tooth remineralization and active treatment by repairing the affected teeth are all methods of managing this process. Treatment options include minimally invasive and adhesive dentistry to full mouth rehabilitation, and restoring the lost vertical height. Case Report: A 45-year-old female patient reported to the Department of Conservative Dentistry and Endodontics with a chief complaint of sensitivity in the upper front teeth for the past 2 months. The clinical examination showed abrasion on the buccal surface of teeth 13 and 23 with dentin exposure. And also, abfraction with respect to 14. No signs of mobility or pain on percussion. Conclusion: The steps of problem identification, diagnosis, etiological factor removal or treatment, and, if necessary, restoration, are components of treating non-caries lesions. The restorative treatment must be considered for dentin hypersensitivity and for the re-establishing of dental esthetics.
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