• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.410-411
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• 2018

In this paper, In this paper, Smart OBD2 terminal collects OBD2 Data on the vehicle. And it passes through this with SmartPhone Bluetooth. OBD2 system is the system to use a variety of Service using it in SmartPhone. Utilizing NFC to help ordinary people, it can easily use to configure the Bluetooth Pairing. By using the Bluetooth 4.0, it is maximized compatibility of Bluetooth. Furthermore OBD2 terminal is a system to minimize the standby power of the terminal to prevent the discharge of the vehicle up issues. Anyone can develop an OBD2 connection App by providing the interfaces to make DB to develop and understand ODB2 data.

• Smart Structures and Systems
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• v.1 no.3
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• pp.235-256
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• 2005

The non-linear behaviour of electrorheological (ER) and magnetorheological (MR) dampers makes it difficult to design effective control strategies, and as a consequence a wide range of control systems have been proposed in the literature. These previous studies have not always compared the performance to equivalent passive systems, alternative control designs, or idealised active systems. As a result it is often impossible to compare the performance of different smart damper control strategies. This article provides some insight into the relative performance of two MR damper control strategies: on/off control and feedback linearisation. The performance of both strategies is benchmarked against ideal passive, semi-active and fully active damping. The study relies upon a previously developed model of an MR damper, which in this work is validated experimentally under closed-loop conditions with a broadband mechanical excitation. Two vibration isolation case studies are investigated: a single-degree-of-freedom mass-isolator, and a two-degree-of-freedom system that represents a vehicle suspension system. In both cases, a variety of broadband mechanical excitations are used and the results analysed in the frequency domain. It is shown that although on/off control is more straightforward to implement, its performance is worse than the feedback linearisation strategy, and can be extremely sensitive to the excitation conditions.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.838-843
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• 2008

Cause of struggling to escape from dependency of fossil fuels, the fuel cell and the Plug-in Hybrid Electric Vehicle (PHEV) draw attention in the all of the world. Especially, the Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems have been anticipated for next generation's energy supplying system, and we can predict the PHEV will enlarge the market share in the next few years to reduce not only the air pollution in the metropolis but the fuel-expenses of commuters. This paper presents simulation results about the strategy of smart charging system for PHEV in the residential house which has 1 kW PEMFC cogeneration system. The smart charging system has a function of recommending the best time to charge the battery of PHEV by the lowest energy cost. The simulated energy cost for charging the battery based on the electricity demand data pattern in the house. The house which floor area is $132\;m^2$ (40 pyeong.). In these conditions, the annual gasoline, electricity, and total energy cost to fuel the PHEV versus Conventional Vehicle (CV) have been simulated in terms of cars' average life span in Korea.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.267-274
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• 2023

LiDAR, one of the most important sensing methods used in mobile robots and cars with assistive/autonomous driving functions, is used to locate surrounding obstacles or to build maps. For real-time path generation, the detection of potholes or puddles on the driving surface is crucial. To achieve this, we used the coordinates of the reflection points provided by LiDAR as well as the intensity information to classify water areas, which was achieved by applying a linear regression method to the intensity distribution. The rationale for using the LiDAR index as an input variable for linear regression is presented, and we demonstrated that it is not affected by errors in the distance measurement value. Because of LiDAR vertical scanning, if the reflective surface is not uniform, it is divided into different groups according to the intensity distribution, and a mathematical basis for this is presented. Through experiments in an outdoor driving area, we could distinguish between flat ground, potholes, and puddles, and kinematic analysis was performed to calculate the maximum width that could be crossed for a given vehicle body size and wheel radius.

• Smart Structures and Systems
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• v.13 no.5
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• pp.755-773
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• 2014

The natural frequency of a bridge is an important parameter in many engineering applications such as bridge seismic design and modal-based bridge health monitoring. The natural frequency of a bridge vibrating alone may differ from that vibrating along with a vehicle. Although such vehicle-induced variability in bridge frequency is revealed in several experimental and numerical simulation studies, few attempts have been made on the theoretical descriptions. In this study, both theoretically and experimentally, the variability in the bridge frequency induced by a parked vehicle is verified, and is therefore suggested to be considered in bridge-related engineering, especially for those cases with near vehicle-bridge resonance conditions or with large vehicle-to-bridge mass ratios. Moreover, the variability ranges could be estimated by an analytical formula presented herein.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1036-1056
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• 2017

The rapid increase of ageing population and chronic disease patients cause high medical expenses, and it led an increased attention to digital healthcare. Smart car technologies for healthcare have been developing to recognize drivers' status and predict diverse driving environments. The present study aimed to understand the research trends of autonomous vehicle technologies of Korea and the United States through time series analysis, network analysis, visualization, and comparison between the two countries. The results suggest that cooperative study needs to be done in common research areas such as driver's safety and algorithms. It is also needed to conduct studies and benchmark about liking technique related to part-to-part and vehicle-to-vehicle as America's competitive advantaged area. In the US, diverse approaches of autonomous vehicle technologies have used to consider the characteristics of various age groups and passengers' health status through sensor, while in Korea, only one aspect, older drivers, is mentioned. Implications for the development direction of autonomous vehicle technologies with competitiveness in considering public health, ethics, and driver's safety and convenience are discussed in detail.

• Smart Media Journal
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• v.10 no.1
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• pp.70-78
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• 2021

The auditory information is used for urgent notification or warning in vehicle because it is not restricted by the direction compared to the visual. However, since the hearing impaired drivers cannot recognize sound signal, various methods of visualizing the auditory information have been attempted to replace it. When visualizing auditory information, only important information should be selected and provided to prevent cognitive overload concentrated on the vision. For this purpose, analysis of the type of auditory information in vehicle should be given in advance. In this study, the types of auditory information in vehicle were analyzed based on the user experience of hearing impaired drivers. Through the observation of the driving behavior of hearing impaired drivers, 33 auditory informations experienced in vehicle were collected. The collected auditory informations were classified into 12 groups through open card sorting by an expert group, and the types of auditory information in vehicle consisting of four levels were presented through a relative comparison of importance between groups. The presented type of auditory information in vehicle can be used as a guideline for selecting important information when the auditory information is converted into visual or tactile. This study is meaningful in that the user experience analysis was conducted by observing actual driving in daily life of hearing impaired drivers.

• Korean Journal of Agricultural Science
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• v.51 no.2
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• pp.133-146
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• 2024

Selection of gear reduction ratio is essential for machine design to ensure suitable power and speed during agricultural operations. The goal of the study was to evaluate the gear reduction ratio for a 1.6 kW four-wheel-drive (4WD) multi-purpose agricultural electric vehicle platform using workload data under different off-road conditions. A data acquisition system was fabricated to collect workload (torque) of the vehicle acting on the gear shaft. Field tests were performed under three driving surfaces (asphalt, concrete, and grassland), payload operations (981, 2,942, and 4,903 N), and slope conditions (0 - 4°, 4 - 8°, and 8 - 12°), respectively. Commercial speed reduction gear phases were attached to the input shaft of the vehicle powertrain. The maximum required torque was recorded as 37.5 Nm at a 4,903 N load with 8 - 12° slope levels, and the minimum torque was 12.32 Nm at 0 - 4° slope levels with a 981 Nm load for a 4 km/h speed on asphalt, concrete, and grassland roads. Based on the operating load condition and motor torque and rotational speed (TN) curve, the minimum and maximum gear reduction ratios were chosen as 1 : 50 and 1 : 64, respectively. The selected motor satisfied power requirements by meeting all working torque criteria with the gear reduction ratios. The chosen motor with a gear reduction ratio of 1 : 50 was suitable to fit with the motor T-N curve, and produced the maximum speeds and loads needed for driving and off-road activities. The findings of the study would assist in choosing a suitable gear reduction ratio for electric vehicle multi-purpose field operations.