• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.126-141
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• 2019

One of the Cooperative Intelligent Transportation System(C-ITS) priority services is collision prevention support service. Several studies have considered V2I2V communication-based collision prevention support services using Artificial Neural Networks(ANN). However, such services still show some issues due to a low penetration of C-ITS devices and large delay, particularly when loading massive traffic data into the server in the C-ITS center. This study proposes the Artificial Neural Network-based Collision Warning Service(ACWS), which allows upstream vehicle to update pre-determined weights involved in the ANN by using real-time sectional traffic information. This research evaluates the proposed service with respect to various penetration rates and delays. The evaluation result shows the performance of the ACWS increases as the penetration rate of the C-ITS devices in the vehicles increases or the delay decreases. Furthermore, it reveals a better performance is observed in more advanced ANN model-based ACWS for any given set of conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.485-492
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• 2010

Intelligent Transport System(ITS) has been studied in various systems, such as road environment information offering, vehicle short-range wireless/wire communication, vehicle collision preventing and pedestrian safety offering systems. Related to this, the USN technology based on the sensing accuracy for motorists and pedestrians safety, the information reliability, the maintenance and convenience for Sensor Network is highlighted. This study uses various sensors to construct USN to the road, and connect it to the developed RSU so it collects the real-time road environment information and offers it to OBU and Traffic Control Surveillance Center with Road Weather Information System. RSU collects roadside information for driver's safety and analyzes it to offer IP and beacon service according to the service priority to OBU & upper layer terminal. In the upper layer terminal it is developed the IP based Settop Box application program to offer the urban traffic information & road environment, and environment sensor error, etc. Finally, RWIS develops the real-time collection of roadside information to complement the driver's safety to the intelligent traffic system, and presents various service modes with technology convergence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1859-1867
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• 2021

Multi LiDAR sensors are being mounted on autonomous vehicles, and a system to multi LiDAR sensors data is required. When sensors data is transmitted or processed to the main processor, a huge amount of data causes a load on the transport network or data processing. In order to minimize the number of load overhead into LiDAR sensor processors, only semantic data is transmitted through data comparison between frames in LiDAR data. When data from 4 LiDAR sensors are processed in a static environment without moving objects and a dynamic environment in which a person moves within sensor's field of view, in a static experiment environment, the transmitted data reduced by 89.5% from 232,104 to 26,110 bytes. In dynamic environment, it was possible to reduce the transmitted data by 88.1% to 29,179 bytes.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.563-570
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• 2024

This paper proposes a method to recognize and track drivable lane areas to assist the driver. The main topic is designing a deep-based network that predicts drivable road areas using computer vision and deep learning technology based on images acquired in real time through a camera installed in the center of the windshield inside the vehicle. This study aims to develop a new model trained with data directly obtained from cameras using the YOLO algorithm. It is expected to play a role in assisting the driver's driving by visualizing the exact location of the vehicle on the actual road consistent with the actual image and displaying and tracking the drivable lane area. As a result of the experiment, it was possible to track the drivable road area in most cases, but in bad weather such as heavy rain at night, there were cases where lanes were not accurately recognized, so improvement in model performance is needed to solve this problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.347-350
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• 2012

The researches on driver assistance systems that can prevent an accident have been actively performed due to social issues of traffic accidents with development of vehicle industry in recent. It is required for researchers to develope systems which assist driver's perception and judgment when considering that over 70% of traffic accidents occur by drivers' carelessness and 75% of the total accidents occur at the speed of less 29km per hour. In this paper, we implemented a front and rear vehicle monitoring system that monitors distance in real-time from a vehicle to obstacles at the low-speed or back-ward driving. The implemented system consists of a high angle ultrasonic sensor with distance detection of 10m and 10-degree angle, a wide angle ultrasonic sensor with the detection distance of 3m and a 180-degree, and a ATmega128 chip of ATmel company.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1903-1909
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• 2011

This paper presents the development of a core module for integrating data from vehicle by the convergence technology of mobile telematics and black-box. This emerging technology can be referred to as Black-box in Mobile (BIM). For the development of BIM, sensors and cameras were realized in a driving robot. Relevant hardware implementation was achieved to verify the functionality of BIM. The transmitted signal from the driving robot was confirmed in an Android-based portable device. Existing Black-boxes were mostly developed by major transportation companies and focused only on storing data. The proposed BIM offers not only data storage but also easy-to-use real-time monitoring while in motion. In addition, the vehicle can be monitored on parking through shock sensors. This development is considered commercially viable as it is achieved via software implementation.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.533-542
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• 2020

In this study, we developed a PC - based motorcycle simulator based on the development technology of the virtual patrol motorcycle training system. In order to get the impression that the motorcycle simulator is operating in a realistic way, it is important to have a reliable signal transmission and operation feeling between the driver and the simulator. In order to achieve this, we developed a system that can apply the sub-systems of the actual vehicle to the motorcycle simulator in order to generate the same operation feeling as the actual vehicle. Based on these results, We have developed a method for generating a feedback queue. Vehicle dynamics simulates real-time vehicle motion by receiving input from a steering wheel, accelerating / decelerating pedal, etc. operated by a driver on a vehicle simulator and transmitting the result to a visual and acoustic system, It is the central element of the simulator to generate. I want to summarize the main requirements of simulation dynamics.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.53-62
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• 2003

This paper demonstrates the in-vehicle dilemma zone warning system (DZWS) project developed as a part of the Driver Advisory and Collision Warning System in Automated Vehicle and Highway System (AVHS). The DZWS project, one of the Korea national ITS projects in 2000 develops the in-vehicle warning device to support drivers' decision making on whether to stop or to proceed to clear the intersection prior to the onset of yellow signal for avoiding the high risk of collision at signalized intersections through the dedicated short range communication (DSRC). This paper explores the design of optimal communication systems between roadway and vehicles, the operational and functional concepts of dilemma zone warning system based on appropriate approach speeds, and the system integration for field test at two sites of signalized intersections. Findings from the system integration indicated that the system would be implemented in eliminating the dilemma zone relative to approach speeds and in reducing red light violations and intersection collisions through the in-vehicle warning device at signalized intersection.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.29-34
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• 2008

Demand for car navigation systems has been an explosive increase because of prevalence of owner-drivers, spare time spread, and so on. In addition, car navigation systems are achieving a rapid growth to be the important part of telematics industry with services such as real-time traffic information and DMB(Digital Multimedia Broadcasting). The network data, one of the composition components in car navigation systems, is most important component because that is abstract of real world road network and base data in pathfinding. However most of the car navigation systems have been stand-alone system. Thus user's network data becomes outdated according to the time passing and does not reflect the change of road information in real world. To overcome this problem, users have to update network data in car navigation systems periodically. This method is quite cumbersome process. For this reason, this study proposed a new update method to serve the difference network data on user's device and the real world in real time, and simulated to verify.