• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.423-433
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• 2017

During recent 5 years, it was recorded that 20% of total accident frequency and 30% of total number of death have been occurred due to drowsy driving. Drowsy driving accident is result from the loss of driving ability due to driver's accumulated fatigue. Continuous driving time can be measured as a surrogate variable to quantify the level of fatigue. The main purpose of this research is to investigate statistical correlation between the proportion of continuous driving vehicle (more than 2 hours) and the number of drowsy accidents. To carry this out, continuous driving time was measured using GPS route-guidance trajectory data. Also, accident frequency, traffic volume and segment length were collected to estimate safety performance function (SPF) for Jungbunearuk expressway in Korea. Through various types of estimated SPFs, statistical correlation was analyzed based on estimated statistical indices. This research can provide theoretical background for enforcement to regulate commercial vehicle driver's continuous driving time. In addition, throughout the trajectory data expansion, it is expected that strategy for anti-drowsy driving facilities installation can be established based on the suggested methodology.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.187-196
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• 2014

In this paper, Minimize driving energy for operation within a defined distance yeokgan fixed time-resolved and determine the nature of the train is traveling, and to model mathematically. Urban rail car cruise in general by the PID controller is used instead of automatically tracking a target value while traveling in energy consumption to be minimized by using optimal control model railroad charyangreul was designed under real operating conditions the same. The actual track conditions apply to the minimum value or a separate listing of cars around the track facility without a driving energy of the automatic operation and to reduce the driving energy. Therefore, actual route chosen straight line 8 / gradient segment / curve for the measured data analysis, such as sections within the city-minute drive each section and presented how the trains to save energy, depending on the pattern of the train station in the region.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.107-114
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• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.35-42
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• 2013

This paper shows the positivistic approach for analyzing the effect of ICT on the reduction of greenhouse gas (GHG) emission. The real-time navigation was selected for the ICT based service in this research, and the CO2 reduction ratios of the optimized routes in the navigation were compared with the reduction ratios of the shortest routes in existing navigations. The results of experiments showed the driving based on the optimized routes has more reduction effects than the driving on the basis of the shortest routes. Also, new evaluation method for GHG emission was suggested by the quantification and monitoring approaches on the basis of the Clean Development Mechanism (CDM) in this paper. The results of this paper can be used as a preliminary research for the effect of ICT on the reduction of GHG emission. The evaluation method which suggested in this paper will be suggested to CDM as the new standard for the reduction of GHG emission in the transportation field as well.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1131-1142
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• 2018

The autonomous vehicles are being developed and operated widely because of the advantages of reducing the traffic accident and saving time and cost for driving. The vehicle localization is an essential component for autonomous vehicle operation. In this paper, localization algorithm based on sensor fusion is developed for cost-effective localization using in-vehicle sensors, GNSS, an image sensor and reference images that made in advance. Information of the reference images can overcome the limitation of the low positioning accuracy that occurs when only the sensor information is used. And it also can acquire estimated result of stable position even if the car is located in the satellite signal blockage area. The particle filter is used for sensor fusion that can reflect various probability density distributions of individual sensors. For evaluating the performance of the algorithm, a data acquisition system was built and the driving data and the reference image data were acquired. Finally, we can verify that the vehicle positioning can be performed with an accuracy of about 0.7 m when the route image and the reference image information are integrated with the route path having a relatively large error by the satellite sensor.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.73-81
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• 2011

The performance of emission factor has been validated by comparison with on-road test data. Emission factor, which is a function of vehicle speed, has been acquired based on chassis dynamometer test with NIER driving pattern. Portable Emission Measurement System, PEMS has measured on-road emission. Test vehicle was operated on defined test routes under different driving conditions, and made ten trips along its route. Emission factors properly simulate on-road test result, although there is some drawback to consider variety of driving condition on real world. Vehicle specific power and acceleration have been used to explain the distributed on-road result within same vehicle speed range. The trend in carbon dioxide and nitrogen oxide emission with respect to specific power and acceleration is clear. It has been found that specific power is a good explanatory variable for microscopic analysis for modal test result. Acceleration is good for microscopic as well as macroscopic analysis.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.657-670
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• 2012

Background: Today, numerous telematics technologies, i.e., technologies developed by integrating telecommunications with information processing, are applied in vehicles. One such developmental application of this technology to vehicles is to increase the safety or convenience of drivers by providing them with necessary information such as warnings and information on emergencies and traffic situations. However, under certain conditions, there is a high probability of traffic accidents if the driving workload is high. Nowadays, the navigation system is frequently used in the vehicles, this system provides various information including route to the driver. But, the existing navigation systems are not only considered a driver's reaction but also provide unilaterally to the information regardless of them. Such one-side information service type may miss important information to the driver. In addition, it sometimes interferes safety driving. Objective: To solve this problem, the intelligent navigation system needs to the providing way that it checks the driver's reactions after providing information. Namely, if the driver passes the information received from the navigation, then the intelligent system provides more loudly and more frequently. Method: Therefore, in this study we introduce the intelligent navigation system that it automatically controls modality type and its strength when the driver misses or overlooks the information for their safety and entertainment and we analyze the driver's cognitive responses about the modality type and its strength. Results: To evaluate the effectiveness of the proposed system, we analyzed the reaction time and driving workload for each type of the information, modality and its strength. Also we evaluated the users' subjective satisfaction and understanding based on a questionnaire.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.76-95
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• 2019

An on-board truck scale is an essential technical solution for preventing overload, which makes the driver aware of the commercial vehicle weight. This study analyzed the effects of the driving pattern and transportation efficiency by the IoT Platform service for an on-board truck scale. A comparison of before and after installation using the long-term monitored data confirmed the reduction effects both of the overload ratio and overweight value, and their effects on increasing the transportation efficiency. In addition, the analysis result of the driving route showed that the installation of an on-board truck scale could be a more effective way of preventing overload than increasing the weighing checkpoints.

• Journal of IKEEE
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• v.27 no.1
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• pp.1-11
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• 2023

Path driving tests are necessary for the development of self-driving cars or robots. These tests are being conducted in simulation as well as real environments. In particular, for development using reinforcement learning and deep learning, development through simulators is also being carried out when data of various environments are needed. To this end, it is necessary to utilize not only manually designed paths but also various randomly and automatically designed paths. This test site design can be used for actual construction and manufacturing. In this paper, we introduce a method for randomly generating a driving test path consisting of a combination of arcs and segments. This consists of a method of determining whether there is a collision by obtaining the distance between an arc and a line segment, and an algorithm that deletes part of the path and recreates an appropriate path if it is impossible to continue the path.

• Knowledge Management Research
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• v.11 no.2
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• pp.75-93
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• 2010

Even though there have been many efforts on driver's route recommendation, driver still should get involved to choose the driving path in a manual manner. Uncertain traffic information provided to the driver delays his arrival time and hence may cause diminished economic values. One of the solutions of reducing the uncertainty is to provide various kinds of traffic information, rather than send real-time information. Therefore, as the wireless communication technology improves and at the same time volume of utilizable traffic contents increases in geometrical progression, selecting traffic information based on driver's context in a timely and individual manner will be needed. Hence, the purpose of this paper is to propose a methodology that efficiently sends the rich traffic contents to the personal in-vehicle navigation. To do so, driver preference is modeled and then the recommendation algorithm of traffic information contents was developed using the preference model. Secondly, ontology based traffic situation analyzation method is suggested to automatically inference the noticeable information from the traffic context on driver's route. To show the feasibility of the idea proposed in this paper, an open API service is implemented in consideration of ease of use.