• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.573-579
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• 2019

To achieve fully autonomous driving, the perceptual skills of the surrounding environment must be superior to those of humans. The $60^{\circ}$ angle, $120^{\circ}$ wide angle cameras, which are used primarily in autonomous driving, have their disadvantages depending on the viewing angle. This paper uses a multi-angle object recognition system to overcome each of the disadvantages of wide and narrow-angle cameras. Also, the aspect ratio of data acquired with wide and narrow-angle cameras was analyzed to modify the SSD(Single Shot Detector) algorithm, and the acquired data was learned to achieve higher performance than when using only monocular cameras.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1396-1406
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• 2018

Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.31-40
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• 2019

In recent years, Intelligent Transport Systems (ITS) and Autonomous Vehicle Technology have actively studied around the world. In order to achieve the purpose of Advanced Driver Assistance System (ADAS) and Autonomous Vehicle Technology, it must be obtained accurate and reliable positioning. However, the problem of positioning in the urban area is a low position accuracy caused by the reduction of the number of visible satellites due to high buildings. In this paper, we analyzed the availability of precise positioning system in urban area are using GPS/BDS integrated system. For this study, GPS and BDS satellite signals were collected using two low-cost receivers in the open sky and a designed software based platform for precise positioning performance analysis. And we analyzed the precise positioning performance by changing the mask angle considering the urban area. From the results, it can be confirmed that the performance of precise positioning of GPS only and BDS only decrease in the environment where mask angle is $40^{\circ}$ to $45^{\circ}$, however, GPS/BDS integrated system maintains high performance of precise positioning.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.1-7
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• 2020

This study is a study on the development of AEBS test scenarios for traffic accidents in Korea, and was compared and analyzed using the Traffic Accident Analysis Program. To ensure the safety of passengers and pedestrians in traffic accidents, the number of cars equipped with ADAS is increasing rapidly at all car manufacturers in each country. For traffic accidents used in this study, the domestic traffic accident database (ACCC) produced by SAMSONG was used. Domestic traffic accidents differ from overseas traffic accidents in terms of road type, signal system, driver's seat location and number of vehicles. ACCC databases, which supplemented and reinforced these differences, built a database based on the PC-CRASH program. In the study, we analyze the types of accidents to develop comparative scenarios for each type of road and collision type of traffic accidents. When the road types of traffic accidents in Korea were divided into five types and the collision types were divided into six, it was confirmed that the most types of FRONT-SIDE crashes appeared at the intersection. It is expected that the frequency of possible traffic accidents and collision types can be predicted according to the road type in the accident database, we that it can be used as an AEBS test scenario development suitable for the domestic road environment.

• Journal of Auto-vehicle Safety Association
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• v.8 no.2
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• pp.6-10
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• 2016

The objective of this paper is to understand value of active safety features on the customer perspective. In this study, 30 participants who don't have experience with active safety features were recruited and asked for preference, usefulness and consideration of each active safety feature after driving evaluation by them. Through this research, the preference of active safety features were analyzed and which of active safety features were the most useful and the most considered by customer when they purchase new vehicle. As a result, adaptive cruise control and side blind zone alert were the most strongly preferred and considered features by respondents and it means that respondents wanted comfort environment while driving and seemed to value features that compensated for limited visibility. On the other hand, active safety features that warned driver without control of the vehicle was deemed generally less desirable such as lane departure warning and forward collision alert. But autonomous emergency braking was higher than the other active safety features with only warning even if they did not have experience for it while this test. They thought it will be helpful in case of front-end collision situation even they just listened description before the test.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.53-58
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• 2023

Defects in the vehicle itself were considered the biggest risk factor for traffic accidents as the electrical and electronic components of vehicles, which were not there before, increase. Therefore, the vehicles have been developed based on ISO 26262 (an international functional safety standard) which is focusing on functional defect safety evaluation of electrical and electronic component systems. However, in the future, as autonomous driving technology is applied, even vehicles without functional defects must be prepared for the dangerous traffic situation that may arise from exceptional or external factors. SOTIF (Safety Of The Intended Functionality) is a concept to prevent exceptional or external factors. The main objective of SOTIF is to decrease Unknown & Unsafe factors as much as possible by finding Known factors and Unsafe factors. In this study, Prescan provided SIEMENS, one of the autonomous driving simulators, is used to make scenarios of IGLAD traffic accident cases. From the simulation results, Unsafe & Safe cases were classified and analyzed to derive unsafe factors.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.59-65
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• 2023

As advanced driving assistance system (ADAS) and autonomous driving performance continue to improve, existing crash accidents and crash types are changing. Accordingly, the collision angle and the seating posture of the occupant are changed. It is necessary to study how the occupant injury mechanism changes according to these different crash types. In this regard, a representative crash test mode was derived when the automatic emergency braking system (AEB), one of the autonomous driving performance, was applied to the representative car-to-car crash scenario in Korea. The derived crash test mode was used to analyse the mechanisms of collision injuries according to both impact angle and the occupant seating posture (reclined seat-back angle). The results obtained through this study can be utilized as reference data for the development of new crash evaluation methods and improvements in crash restraint systems for enhancing crash safety.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.6-12
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• 2023

For the commercialization and standardization of autonomous vehicles, demand for rigorous safety criteria has been increased over the world. In Korea, the number of extraordinary service permission for automated vehicles has risen since Hyundai Motor Company got its initial license in March 2016. Nevertheless, licensing standards and evaluation factors are still insufficient for operating on public roadways. To assure driving safety, it is significant to verify whether or not the vehicle's decision is similar to human driving. This paper validates the safety of the autonomous vehicle by drawing scenario-based comparisons between manual driving and autonomous driving. In consideration of real traffic situations and safety priority, seven scenarios were chosen and classified into basic and advanced scenarios. All scenarios and safety factors are constructed based on existing ADAS requirements and investigated via a computer simulation and actual experiment. The input data was collected by an experimental vehicle test on the SNU FMTC test track located at Siheung. Then the offline simulation was conducted to verify the output was appropriate and comparable to the manual driving data.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.252-263
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• 2016

Road sign is an important street furniture that gives some information such as road conditions, driving direction and condition for a driver. Thus, road sign is a major target of image recognition for self-driving car, ADAS(autonomous vehicle and intelligent driver assistance systems), and ITS(intelligent transport systems). In this paper, an enhanced road sign recognition system is proposed for MMS(Mobile Mapping System) using the single camera and GPS. For the proposed system, first, a road sign recognition scheme is proposed. this scheme is composed of detection and classification step. In the detection step, object candidate regions are extracted in image frames using hybrid road sign detection scheme that is based on color and shape features of road signs. And, in the classification step, the area of candidate regions and road sign template are compared. Second, a Geo-marking scheme for geo-content that is consist of road sign image and coordinate value is proposed. If the serious situation such as car accident is happened, this scheme can protect geographical information of road sign against illegal users. By experiments with test video set, in the three parts that are road sign recognition, coordinate value estimation and geo-marking, it is confirmed that proposed schemes can be used for MMS in commercial area.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.126-136
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• 2014

In the Advanced Driver Assistance Systems (ADAS) of smart vehicle and Intelligent Transportation System (ITS) for to detect the boundary of lane is being studied a lot of Hough Transform. This method detects correctly recognition the lane. But recognition rate can fall due to detecting straight lines outside of the lane. In order to solve this problems, this paper proposed an algorithm to recognize the lane boundaries and the accumulator cells in Hough space. Based on proposed algorithm, we develop application for Android was developed by H/W verification. Users of smart phone devices could use lane detection and lane departure warning systems for driver's safety whenever and wherever. Software verification using the OpenCV showed efficiency recognition correct rate of 93.8% and hardware real-time verification for an application development in the Android phone showed recognition correct rate of 70%.