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The delivery market in Republic of Korea has experienced significant growth, leading to a surge in motorcycle-related accidents. However, there is a lack of comprehensive data collection systems for motorcycle safety management. This study focused on designing and implementing a foundational data collection system to monitor and evaluate motorcycle driving behavior. To achieve this, eleven risky behaviors were defined, identified using image-based, GIS-based, and inertial-sensor-based methods. A motorcycle-mounted sensing device was installed to assess driving, with drivers reviewing their patterns through an app and all data monitored via a web interface. The system was applied and tested using a testbed. This study is significant as it successfully conducted foundational data collection for motorcycle safety management and designed and implemented a system for monitoring and evaluation. [ABSTRACT FROM AUTHOR]

An interpolation method, which estimates unknown values with constrained information, is based on mathematical calculations. In this study, we addressed interpolation from an image-based perspective and expanded the use of image inpainting to estimate values at unknown points. When chemical gas is dispersed through a chemical attack or terrorism, it is possible to determine the concentration of the gas at each location by utilizing the deployed sensors. By interpolating the concentrations, we can obtain the contours of gas concentration. Accurately distinguishing the contours of a contaminated region from a map enables the optimal response to minimize damage. However, areas with an insufficient number of sensors have less accurate contours than other areas. In order to achieve more accurate contour data, an image inpainting-based method is proposed to enhance reliability by erasing and reconstructing low-accuracy areas in the contour. Partial convolution is used as the machine learning approach for image-inpainting, with the modified loss function for optimization. In order to train the model, we developed a gas diffusion simulation model and generated a gas concentration contour dataset comprising 100,000 contour images. The results of the model were compared to those of Kriging interpolation, one of the conventional spatial interpolation methods, finally demonstrating 13.21% higher accuracy. This suggests that interpolation from an image-based perspective can achieve higher accuracy than numerical interpolation on well-trained data. The proposed method was validated using gas concentration contour data from the verified gas dispersion modeling software Nuclear Biological Chemical Reporting And Modeling System (NBC_RAMS), which was developed by the Agency for Defense Development, South Korea. [ABSTRACT FROM AUTHOR]

The diversification of mobility into services such as smart stores and conference rooms has accelerated the development of purpose-built vehicles (PBVs)—vehicles designed for specific purposes that utilize an extended electric vehicle chassis and autonomous driving technology. Despite the standards on speed bump dimensions stipulated by the National Land Transportation Act of the Republic of Korea, real-world speed bumps feature varying widths and heights that deviate from these standards. In this study, a velocity equation was derived via regression analysis to achieve the desired dynamic characteristics for a PBV passing over speed bumps with varying shapes through two types of semi-active suspension control: proportional–integral–differential (PID) and linear–quadratic–regulator (LQR). For a cargo-transport PBV, the PID and LQR controllers increased the velocity by 23.74% and 50.74%, respectively, under different speed bump widths and by 19.44% and 38.31%, respectively, under different speed bump heights. Moreover, an analysis of the vibration dose value (VDV), an indicator of ride comfort, revealed that the VDVs calculated using the velocity equation were within an acceptable error range of 10% above the target VDV. These findings provide insights into the speed control required for different types of autonomous PBVs to ensure ride comfort, as well as minimize the driving duration, depending on the specific purpose of the vehicle. [ABSTRACT FROM AUTHOR]