The purpose of the present study was to gain a better understanding of the types of in-vehicle technologies being used by older drivers as well as older drivers' use, learning, and perceptions of safety related to these technologies among a large cohort of older drivers at multiple sites in the United States. A secondary purpose was to explore the prevalence of aftermarket vehicle adaptations and how older adults go about making adaptations and how they learn to use them. The study utilized baseline questionnaire data from 2990 participants from the Longitudinal Research on Aging Drivers (LongROAD) study. Fifteen in-vehicle technologies and 12 aftermarket vehicle adaptations were investigated. Overall, 57.2% of participants had at least one advanced technology in their primary vehicle. The number of technologies in a vehicle was significantly related to being male, having a higher income, and having a higher education level. The majority of respondents learned to use these technologies on their own, with "figured-it-out-myself" being reported by 25%-75% of respondents across the technologies. Overall, technologies were always used about 43% of the time, with wide variability among the technologies. Across all technologies, nearly 70% of respondents who had these technologies believed that they made them a safer driver. With regard to vehicle adaptations, less than 9% of respondents had at least one vehicle adaptation present, with the number of adaptations per vehicle ranging from 0 to 4. A large majority did not work with a professional to make or learn about the aftermarket vehicle adaptation.
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http://dx.doi.org/10.1016/j.aap.2018.01.022 | DOI Listing |
Biomimetics (Basel)
January 2025
Robotics and Microsystems Center, College of Mechanical and Electrical Engineering, Soochow University, Suzhou 215021, China.
Flapping wing micro aerial vehicles (FWMAVs) are recognized for their significant potential in military and civilian applications, such as military reconnaissance, environmental monitoring, and disaster rescue. However, the lack of takeoff and landing capabilities, particularly in landing behavior, greatly limits their adaptability to the environment during tasks. In this paper, the purple stem beetle (), a natural flying insect, was chosen as the bionic research object.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Technology Research and Development Centre, Xuelong Group Co., Ltd., Ningbo 315899, China.
To address the challenges of slow convergence speed, poor convergence precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a path planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). First, a mathematical model is used to construct a three-dimensional terrain environment, and a multi-constraint path cost model is established, framing path planning as a multidimensional function optimization problem. Second, recognizing the sensitivity of population diversity to Logistic Chaotic Mapping in a traditional Human Evolution Optimization Algorithm (HEOA), an opposition-based learning strategy is employed to uniformly initialize the population distribution, thereby enhancing the algorithm's global optimization capability.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Guangdong University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou, China.
Precise segmentation of unmanned aerial vehicle (UAV)-captured images plays a vital role in tasks such as crop yield estimation and plant health assessment in banana plantations. By identifying and classifying planted areas, crop areas can be calculated, which is indispensable for accurate yield predictions. However, segmenting banana plantation scenes requires a substantial amount of annotated data, and manual labeling of these images is both timeconsuming and labor-intensive, limiting the development of large-scale datasets.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Public Health, University of California, Merced, 5200 N Lake Road, Merced, CA, 95343, USA.
Background: The San Joaquin Valley (SJV) in California is one of the most polluted regions in the U.S. This study examined favorability for air pollution mitigation policies, interventions, and identified predictors amongst region's residents.
View Article and Find Full Text PDFISA Trans
January 2025
College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, Hunan, China. Electronic address:
Approximation-free control effectively addresses uncertainty and disturbances without relying on approximation techniques such as fuzzy logic systems (FLS) and neural networks (NNs). However, singularity problems-where signals exceed preset boundaries under dynamic operating conditions-remain a challenge. This paper proposes an improved approximation-free control (I-AFC) method for the multi-agent system, which introduces a novel singularity compensator, providing a low-complexity design with exceptional adaptability while reducing the risk of singularity issues under changing working conditions (random initial values, system parameter variations, and changes in topology graph and followers' dynamics).
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