• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.116-129
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• 2023

Recently, interest in autonomous driving has drawn attention to autonomous cooperative driving, which considers the development of driving technology of autonomous vehicles and the development of infrastructure that constitutes a driving environment. According to the concept of autonomous cooperative driving, This study analyzes the new infrastructure for autonomous driving that can complement the information of existing precise road maps and adding HD map layer as the new infrastructure. The new infrastructure for autonomous driving presented two types of improved facilities and one type of sensor only facility. Analysis of HD maps shows that information such as junction points rarely changes, but it is expected that infrastructure for autonomous driving can be added to convey the meaning of paying attention to obstacles that may arise at the junction. In this way, the new infrastructure for autonomous driving needs to support the roles of guidance, instruction, and attention that existing road facilities.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.179-187
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• 2011

Multiple roadmap DB providers are already available in these days, and try to reduce unknown roads in their own roadmaps. However, cooperation models or Win-Win approaches between roadmap providers are not considered yet. Thus, In this paper, We proposed a cloud-oriented real-time roadmap generation and update method between heterogeneous navigation systems for unknown roads. With the proposed method, the roadmap DB providers update the own roadmap DB for navigation systems in real time. Also, they can provide the complete roadmap without unknown roads to users instantly. Therefore, the proposed method can reduce the costs of an actual traveling test and the maintenance for the roadmap DB provides. Thus, the cloud-oriented roadmap generation method can more efficiently update the unknown road information.

• 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 Society of Computer and Information
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• v.12 no.1 s.45
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• pp.189-197
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• 2007

Developed safety system which transfers danger information to rear cars for accident prevention when drivers detect a accident, a dropping or a freezing during driving on the high way. To prevent an accident, each vehicles mount OBU which is made up of a GPS unit and a transmitter-receiver and the trace of road is always renewed and saved in OBU per a regular past distance. When the driver see dangerous situation, transfer a danger pattern and a trace information by pressing button. All cars which receive information compare the received data with the original data. And then, only cars which are located at the rear in a regular distance respond and occur a warning. Performed a road test at the rate of $30{\sim}50$ kilometer a hour using two test cars which saved about 120meter's space between them were mounted OBU which had 447Mhz transceiver. As a result of the experiment, communication between test cars had no problem. Accordingly, it can use a safety driving device because driver can notice a danger situation and set themselves ready for it using this system in advance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.102-116
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• 2021

For the safe operation of autonomous vehicles, the representative technology of the 4^th industrial revolution era, a combination of various technologies such as sensor technology, software technology and car technology is required. An autonomous vehicle is a vehicle that recognizes current location and situation by using the various sensors, and makes its own decisions without depending on the driver. Perfect recognition technology is required for fully autonomous driving. Since the precise road maps provide various road information including lanes, stop lines, traffic lights and crosswalks, it is possible to minimize the cognitive errors that occur in autonomous vehicles by using the precise road maps with location information of the road facilities. In this study, the definition, necessity and technical trends of the precise road map have been analyzed, and the HD(High Definition) map prototype based on the web GIS has been built in the autonomous driving-specialized areas of Daegu Metropolitan City(Suseong Medical District, about 24km), the Happy City of Sejong Special Self-Governing City(about 33km), and the FMTC(Future Mobility Technical Center) PG(Proving Ground) of Seoul National University Siheung Campus using the MMS(Mobile Mapping System) surveying results given by the National Geographic Information Institute. In future research, the built-in precise road map service will be installed in the autonomous vehicles and control systems to verify the real-time locations and its location correction algorithm.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.28-37
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• 2009

In this paper, we propose an obstacle localization method using a road feature based on a V-disparity map binarized by a maximum frequency value. In a conventional method, the detection performance is severely affected by the size, number and type of obstacles. It's especially difficult to extract a large obstacle or a continuous obstacle like a median strip. So we use a road feature as a new decision standard to localize obstacles irrespective of external environments. A road feature is proper to be a new decision standard because it keeps its rough feature very well in V-disparity under environments where many obstacles exist. And first of all, we create a binary V-disparity map using a maximum frequency value to extract a road feature easily. And then we compare the binary V-disparity map with a median value to remove noises. Finally, we use a linear interpolation for rows which have no value. Comparing this road feature with each column value in disparity map, we can localize obstacles robustly. We also propose a post-processing technique to remove noises made in obstacle localization stage. The results in real road tests show that the proposed algorithm has a better performance than a conventional method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.74-88
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• 2020

A Cooperative Intelligent Transportation System (CITS) provides useful information on upcoming hazards in order to prevent vehicle collisions. In addition, the availability of individual vehicle travel information obtained from the CITS infrastructure allows us to identify the level of road safety in real time and based on analysis of the indicators representing the crash potential. This study proposes a methodology to derive road safety content, and presents evaluation results for its applicability in practice, based on simulation experiments. Both jerk and Stopping Distance Index (SDI) were adopted as safety indicators and were further applied to derive road section safety information. Microscopic simulation results with VISSIM show that 5% and 20% samples of jerk and SDI are sufficient to represent road safety characteristics for all vehicles. It is expected that the outcome of this study will be fundamental to developing a novel and valuable system to monitor the level of road safety in real time.