Collision avoidance technology has the capacity to facilitate safer mobility among older power mobility users with physical, sensory, and cognitive impairments, thus enabling independence for more users. Little is known about consumers' perceptions of collision avoidance. This article draws on interviews (29 users, 5 caregivers, and 10 prescribers) to examine views on design and utilization of this technology. Data analysis identified three themes: "useful situations or contexts," "technology design issues and real-life application," and "appropriateness of collision avoidance technology for a variety of users." Findings support ongoing development of collision avoidance for older adult users. The majority of participants supported the technology and felt that it might benefit current users and users with visual impairments, but might be unsuitable for people with significant cognitive impairments. Some participants voiced concerns regarding the risk for injury with power mobility use and some identified situations where collision avoidance might be beneficial (driving backward, avoiding dynamic obstacles, negotiating outdoor barriers, and learning power mobility use). Design issues include the need for context awareness, reliability, and user interface specifications. User desire to maintain driving autonomy supports development of collaboratively controlled systems. This research lays the groundwork for future development by illustrating consumer requirements for this technology.
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http://dx.doi.org/10.1682/JRRD.2012.10.0181 | DOI Listing |
Sensors (Basel)
January 2025
Seamless Trans-X Lab (STL), School of Integrated Technology, Yonsei University, Incheon 21983, Republic of Korea.
In the domain of autonomous driving, trajectory prediction plays a pivotal role in ensuring the safety and reliability of autonomous systems, especially when navigating complex environments. Unfortunately, trajectory prediction suffers from uncertainty problems due to the randomness inherent in the driving environment, but uncertainty quantification in trajectory prediction is not widely addressed, and most studies rely on deep ensembles methods. This study presents a novel uncertainty-aware multimodal trajectory prediction (UAMTP) model that quantifies aleatoric and epistemic uncertainties through a single forward inference.
View Article and Find Full Text PDFHealth Phys
January 2025
Division of Vision Research for Environmental Health, Medical Research Institute and Department of Ophthalmology, Kanazawa Medical University, Kahoku, Japan.
Electromagnetic radiation energy at millimeter wave frequencies, typically 30 GHz to 300 GHz, is ubiquitously used in society in devices for telecommunications; radar and imaging systems for vehicle collision avoidance, security screening, and medical equipment; scientific research tools for spectroscopy; industrial applications for non-destructive testing and precise measurement; and military and defense applications. Understanding the biological effects of this technology is essential. We have been investigating ocular responses and damage thresholds comparing various frequencies using rabbit eyes and dedicated experimental apparatus.
View Article and Find Full Text PDFSci Rep
January 2025
Commercial Product R&D Institute, Dongfeng Automobile Co., Ltd., Wuhan, 430070, People's Republic of China.
The rapid acceleration of urbanization and the surge in car ownership necessitate efficient automatic parking solutions in constricted spaces to address the escalating urban parking issue. To optimize space utilization, enhance traffic efficiency, and mitigate accident risks, a method is proposed for smooth, comfortable, and adaptable automatic parking trajectory planning. This study initially employs a hybrid A* algorithm to generate a preliminary path, then fits the velocity and acceleration based on a cubic polynomial.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Japan.
With the decreasing and aging agricultural workforce, fruit harvesting robots equipped with higher degrees of freedom (DoF) manipulators are seen as a promising solution for performing harvesting operations in unstructured and complex orchard environments. In such a complex environment, guiding the end-effector from its starting position to the target fruit while avoiding obstacles poses a significant challenge for path planning in automatic harvesting. However, existing studies often rely on manually constructed environmental map models and face limitations in planning efficiency and computational cost.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Hubei Province Engineering Technology Research Center for Construction Quality Testing Equipments, College of Computer and Information Technology, China Three Gorges University, Yichang 443002, China.
With the widespread use of autonomous guided vehicles (AGVs), avoiding collisions has become a challenging problem. Addressing the issue is not straightforward since production efficiency, collision avoidance, and energy consumption are conflicting factors. This paper proposes a novel edge computing method based on vehicle edge intelligence to solve the energy-efficient collision-free machine/AGV scheduling problem.
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