• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.696-704
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• 2011

In this paper, we propose a mobile robot navigation algorithm using data fusion of a monocular camera and ultrasonic sensors. Threshold values for binary image processing are generated by a fuzzy inference method using image data and data of ultrasonic sensors. Threshold value variations improve obstacle detection for mobile robot to move to the goal under poor illumination environments. Obstacles detected by data fusion of camera and ultrasonic sensors are expressed on the grid map and avoided using the circular planning algorithm. The performance of the proposed method is evaluated by experiments on the Pioneer 2-DX mobile robot in the indoor room with poor lights and a narrow corridor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.799-808
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• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.13-20
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• 2022

It's proposed and analyzed ML(Machine Learning) models to predict vehicle FC(Fuel Consumption) in real-time. The test driving was done for a car to measure vehicle speed, acceleration, road gradient and FC for training dataset. The various ML models were trained with feature data of speed, acceleration and road-gradient for target FC. There are two kind of ML models and one is regression type of linear regression and k-nearest neighbors regression and the other is classification type of k-nearest neighbors classifier, logistic regression, decision tree, random forest and gradient boosting in the study. The prediction accuracy is low in range of 0.5 ~ 0.6 for real-time FC and the classification type is more accurate than the regression ones. The prediction error for total FC has very low value of about 0.2 ~ 2.0% and regression models are more accurate than classification ones. It's for the coefficient of determination (R²) of accuracy score distributing predicted values along mean of targets as the coefficient decreases. Therefore regression models are good for total FC and classification ones are proper for real-time FC prediction.

• Journal of Auto-vehicle Safety Association
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• v.4 no.1
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• pp.5-11
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• 2012

This paper discusses the evaluation of the safety impact of the Adaptive Cruise Control (ACC) system in Korea. To evaluate the safety impact, this paper suggests an analysis method by using the test scenario and field operational test data. The test scenario is composed to represent the main component factor of the ACC system and ACC related accident situation such as rear-end collision, lane-change, and road-curvature, etc. Also, from the field operation test data, the system's potential to increase the safety can be measured ideally. Besides, field operational testdata was used to revise the expected safety impact value as Korean road conditions. By using the proposed evaluation method, enhanced safety impact of the ACC system can be estimated scientifically.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.370-376
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• 2022

Smart ships related studies are being conducted in various fields owing to the development of technology, and an engine room patrol robot that can patrol the unmanned engine room is one such study. A patrol robot moves around the engine room based on the information learned through artificial intelligence and checks the machine normality and occurrence of abnormalities such as water leakage, oil leakage, and fire. Study on engine room patrol robots is mainly conducted on machine detection using artificial intelligence, however study on movement and control is insufficient. This causes a problem in that even if a patrol robot detects an object, there is no way to move to the detected object. To secure maneuverability to quickly identify the presence of abnormality in the engine room, this study experimented with whether a patrol robot can determine the shortest path by applying the A* algorithm. Data were obtained by driving a small car equipped with LiDAR in the ship engine room and creating a map by mapping the obtained data with SLAM(Simultaneous Localization And Mapping). The starting point and arrival point of the patrol robot were set on the map, and the A* algorithm was applied to determine whether the shortest path from the starting point to the arrival point was found. Simulation confirmed that the shortest route was well searched while avoiding obstacles from the starting point to the arrival point on the map. Applying this to the engine room patrol robot is believed to help improve ship safety.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.12
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• pp.965-973
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• 2015

Recently, an emission test procedure using a portable emissions measurement system(PEMS) has received much attention as an effective means of controlling real driving emissions from light-duty diesel vehicles. The PEMS-based test procedure will be implemented from 2017 in Europe and Korea as a complementary test procedure for certification and regulation. In the present study, on-road NOx emissions were measured for four kinds of Euro 5 Korean light-duty diesel vehicles under real driving conditions, including urban, rural, and motorway test routes. The real driving emission characteristics were evaluated using both a moving averaging window(MAW) and the weighted emission method(WEM). The evaluated NOx emission results (under real driving conditions) from the MAW and WEM showed similar tendencies for the test vehicles and routes, while exceeding the certification emission limit by 1.8~8.5 and 2.0~10.6 times, respectively.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.25-38
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• 2010

In this study, the real on-road driving data were analyzed to draw the various characteristics related to idling of vehicles. The results revealed that the average idling time of a city bus corresponds to 30.9% of the total daily driving time. Among this, for about 21.6% of the total daily driving time, it is available that an engine can be halted while the vehicle stops. It is a daytime when the portion of time, for which idling stop is available, is peak. Due to idling stop, an increase of turnaround was not found throughout this analysis. When a city bus stops at a traffic right, idling periods were long enough to execute the idling stop, during which an engine halts. Whereas, during the idling time for bus stops, the idling periods were not so long enough to execute idling stop. Deceleration periods among the total turnarounds of a city bus occupies about 24.7%, during which, for about 30%, a deceleration maintains for more than four seconds. Thus, using the energy during deceleration period, which then can be recovered from braking energy, it was also found that a hybrid system can be effectively implemented to a city bus.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.133-140
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• 2016

The Ministry of Land, Infrastructure and Transport has introduced low-floor buses, which are convenient for passengers getting on and off the bus and for the handicapped. The standard bus model is 11 m long and uses compressed natural gas (CNG). However, this model has drawbacks in narrow rural road conditions such as those in farming and fishing villages and mountainous areas, as well as difficulty in refueling since CNG facilities are not readily available. In this study, running resistance values were obtained by coasting performance tests on actual roads using a Tata Daewoo LF-40 model with three different weight conditions: curb vehicle weight (CVW), half vehicle weight (HVW), and gross vehicle weight (GVW).The test methods include WHVC, NIER-06, and constant-speed driving at 60 km/h. These tests were used to measure the fuel economy of vehicles other than the target vehicles to obtain the combined fuel economy. The energy efficiency was highest in the case of CVW. In the WHVC mode, the fuel consumption rates of HVW and GVW were typically 3.5% and 12% higher than that of CVW, respectively. In constant-speed driving, the fuel efficiency of HVW was higher than that of CVW. Further research is required to analyze the exhaust gas data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.48-56
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• 2008

This study provides to car driver with car exhaust gas and sensor information which are car trouble code in engine and many sensors when the car has some problems. This is to provide car manager with many information of car sensors when we go to vehicle maintenance. For example, information of engine RPM, fuel system, intake air temperature, air flow sensors and oxygen sensors can provide to owner or garage, and also add to multimedia system for mp3 files and video files. This system consists of embedded linux system of low power while driving the car which uses OBD-II protocols and zigbee communication interface from CAN communication of car system to self-diagnosis embedded system of car. Finally, low power embedded system has a lot of application and OBD-II protocols for embedded linux system and CAN communication which get sensor informations of car control sensor system while driving the car.