A Convergence Study on a Smart Helmet Design for Safe Riding of Personal Mobility Users_Focused on Lighting Interaction

2020 ◽  
Vol 38 (5) ◽  
pp. 297-316
Author(s):  
So Young An ◽  
Eun Young Kim
1999 ◽  
Author(s):  
Mary E. Gross ◽  
Bruce Bradtmiller
Keyword(s):  

2013 ◽  
Vol 133 (3) ◽  
pp. 282-289
Author(s):  
Noriaki Hirose ◽  
Ryosuke Tajima ◽  
Kazutoshi Sukigara ◽  
Yuji Tsusaka

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 437
Author(s):  
Yuya Onozuka ◽  
Ryosuke Matsumi ◽  
Motoki Shino

Detection of traversable areas is essential to navigation of autonomous personal mobility systems in unknown pedestrian environments. However, traffic rules may recommend or require driving in specified areas, such as sidewalks, in environments where roadways and sidewalks coexist. Therefore, it is necessary for such autonomous mobility systems to estimate the areas that are mechanically traversable and recommended by traffic rules and to navigate based on this estimation. In this paper, we propose a method for weakly-supervised recommended traversable area segmentation in environments with no edges using automatically labeled images based on paths selected by humans. This approach is based on the idea that a human-selected driving path more accurately reflects both mechanical traversability and human understanding of traffic rules and visual information. In addition, we propose a data augmentation method and a loss weighting method for detecting the appropriate recommended traversable area from a single human-selected path. Evaluation of the results showed that the proposed learning methods are effective for recommended traversable area detection and found that weakly-supervised semantic segmentation using human-selected path information is useful for recommended area detection in environments with no edges.


2021 ◽  
Vol 13 (3) ◽  
pp. 1270
Author(s):  
Sung Il Kwag ◽  
Uhjin Hur ◽  
Young Dae Ko

Though new technologies have been applied in all industries, electric mobility technology using eco-friendly energy is drawing a great deal of attention. This research focuses on a personal electric mobility system for urban tourism. Some tourism sites such as Gyeongju, Korea, have broad spaces for tourists to walk around, but the public transportation system has been insufficiently developed due to economic reasons. Therefore, personal mobility technology such as electric scooters can be regarded as efficient alternatives. For the operation of electric scooters, a charging infrastructure is necessary. Generally, scooters can be charged via wires, but this research suggests an advanced electric personal mobility system based on wireless electric charging technology that can accommodate user convenience. A mathematical model-based optimization was adopted to derive an efficient design for a wireless charging infrastructure while minimizing total investment costs. By considering the type of tourists and their tour features, optimal locations and lengths of the static and dynamic wireless charging infrastructure are derived. By referring to this research, urban tourism can handle transportation issues from a sustainable point of view. Moreover, urban tourism will have a better chance of attracting tourists by conserving heritage sites and by facilitating outdoor activities with electric personal mobility.


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