• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.249-255
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• 2018

This paper presents a human-centered control algorithm for personalized autonomous driving based on the integration of inverse time-to-collision and time headway. In order to minimize the sense of difference between driver and autonomous driving, the human-centered control technology is required. Driving characteristics in case that vehicle drives with the preceding vehicle have been analyzed and reflected to the longitudinal control algorithm. The driving characteristics such as acceleration, inverse time-to-collision, time headway have been analyzed for longitudinal control. The control algorithm proposed in this study has been constructed on Matlab/Simulink environment and the performance evaluation has been conducted by using actual driving data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.172-185
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• 2021

As the era of autonomous driving approaches, it is expected to have a significant impact on our lives. When autonomous driving cars emerge, it is necessary to develop an index that can evaluate autonomous driving cars as it enhance the productive value of the car by reducing the burden on the driver. This study analyzed how the autonomous driving era affects commuting time and commuting time satisfaction among office goers using a car in Gyeonggi-do. First, a nonlinear relationship (V) was derived for the commuting time and commuting time satisfaction. Here, the factors affecting commuting time satisfaction were analyzed through a binomial logistic model, centered on the sample belonging to the nonlinear section (70 minutes or more for commuting time), which is likely to be affected by the autonomous driving era. The analysis results show that the variables affected by the autonomous driving era were health, sleeping hours, working hours, and leisure time. Since the emergence of autonomous driving cars is highly likely to improve the influencing variables, long-distance commuters are likely to feel higher commuting time satisfaction.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.798-801
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• 2014

여행 정보 시스템(ATIS), 교통 관리 시스템 (ITS) 등 궤적 기반 서비스에서, 서비스 품질을 향상시키기 위해서는 주어진 궤적 질의에 대한 정확한 주행시간을 예측하는 것이 필수적이다. 이를 위한 대표적인 공간 데이터 분석 기법으로는 데이터 분류에서 높은 정확도를 보장하는 규칙 기반 분류화 기법이 존재한다. 그러나 기존 규칙 기반 분류화 기법은 단일 컴퓨터 환경만을 고려하기 때문에, 대용량 공간 데이터 처리에 적합하지 않은 문제점이 존재한다. 이를 해결하기 위해, 본 연구에서는 맵리듀스 환경에서 규칙 기반 분류화를 이용한 궤적 데이터 주행 시간 예측 알고리즘을 개발하고자 한다. 제안하는 알고리즘은 첫째, 맵리듀스를 이용하여 대용량 공간 데이터를 병렬적으로 분석함으로써, 활용도 높은 궤적 데이터 규칙을 생성한다. 이를 통해 대용량 공간 데이터 기반의 규칙 생성 시간을 감소시킨다. 둘째, 그리드 구조 기반의 지도 데이터 분할을 통해, 사용자 질의처리 시 탐색 성능을 향상시킨다. 즉, 주행 시간 예측을 위한 규칙 그룹을 탐색 시 질의를 포함하는 그리드 셀만을 탐색하기 때문에, 질의처리 성능이 향상된다. 마지막으로 맵리듀스 구조에 적합한 질의처리 알고리즘을 설계하여, 효율적인 병렬 질의처리를 지원한다. 이를 위해 맵 함수에서는 선정된 그리드 셀에 대해, 질의에 포함된 도로 구간에서의 주행 시간을 병렬적으로 측정한다. 아울러 리듀스 함수에서는 출발 시간 및 구간별 주행 시간을 바탕으로 맵 함수의 결과를 병합함으로써, 최종 결과를 생성한다. 이를 통해 공간 빅데이터 분석을 통한 주행 시간 예측 기법의 처리 시간 및 결과 정확도를 향상시킨다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.77-86
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• 2016

Drivers can receive diverse types of traffic information through a number of methods. However, there are not enough information services considering human factors. In this study, as a basic research on human factors of the drivers, characteristic analysis on drivers' mean glance (fixation) durations with different running speeds on the expressway was performed under diverse running environments. To control variables other than running speeds, running environments were categorized into 4 types: 'daytime running without preceding vehicles', 'daytime running with preceding vehicles', 'nighttime running without preceding vehicles', and 'nighttime running with preceding vehicles'. Furthermore, ANOVA Test was used to divide speed groups. As a result of performing a multiple comparison to compare differences in glance behavior per each group, the road item and the preceding vehicles item showed an increase in mean glance durations as the speed increased, while the front view showed a decrease in mean glance durations. It was confirmed that the road sign showed no statistically significant difference in glance durations as the speed varied.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.413-417
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• 2005

본 연구에서는 설계속도별 연속류 흐름을 가진 대상도로를 선택하여, 대상도로의 비첨두 시간을 정하여, 동영상에 의한 촬영을 실시하여 구간 주행속도를 추출하는 연구를 수행하였다. 각 대상구간의 거리는 수치지도 및 측량, 주행기록계 등을 이용하여 측정하였고, 영상의 분석을 통하여 차량의 구간통과시간을 산정하여 설계속도별 주행속도를 추출하였다. 그에 대한 검증으로 차량의 DGPS를 장착하여 대상도로를 주행하면서 동영상에 의한 주행속도와 비교 검증을 실시하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.235-249
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• 2020

The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.167-189
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• 2022

In the case of SAE autonomous driving levels 2 and 3, since complete autonomous driving is impossible, the take-over process is essential, and take-over time(TOT) is the most important factor in determining the safety of the autonomous driving system. Accordingly, research on TOT is being actively conducted, but each research is independently conducted and general conclusions that integrate various research results are required. Therefore, in this study, the factors affecting TOT were analyzed using meta-analysis, which integrates the results of individual studies and presents an integrated opinion. As a result of meta-analysis, a total of 10 influencing factors were selected, and most of them were related to the non-driving related task(NDRT) type. In addition, implications for the future research direction of take-over and NDRT were presented.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.7-14
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• 2018

The purpose of this study is to analyze the effect of commuter's departure time on transportation system in future traffic system operated autonomous vehicle using agent based model. Various scenarios have been set up, such as when all passenger choose a similar departure time, or if the passenger chooses a different departure time. Also, this study tried to analyze the effect of road capacity. It was found that although many of the scenarios had been completed in a stable manner, many commuters were significantly coordinated at the desired departure time. In particular, in the case of a reduction in road capacity or in certain scenarios, it has been shown that, despite excessive schedule adjustments, many passengers are unable to commute before 9 o'clock. As a result, it is suggested that traffic management and pricing policies are different from current ones in the era of autonomous car operation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.147-156
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• 2017

This paper analyzes the performance limit of WAVE system for the platooning service requirements which is referred from the de facto standards. The performance of the packet error rate and mean delay as key parameters in the wireless communication systems should be satisfied to provide safety to the platooning vehicles. The test scenarios are conducted by considering the following vehicle groups: platooning vehicles, vehicles within a hop distance and vehicles within two hop distance( called hidden node vehicles). The models of packet error rate and delay deals with the topology of aforementioned vehicle groups, vehicle speed and communication range. The numerical results are obtained in terms of packet size, packet arrival rate and data transmission rate. Finally, this paper suggests the robust range of packet error rate and delay for the WAVE system to provide the platooning vehicle service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.681-687
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• 2017

We investigated the potential for wind-power generation using the wind produced by express trains. We built equipment to detect the wind velocity, including wind meters and a data analyzer. We considered various conditions that might change the wind. First, we measured the velocity and duration of the wind at three locations distinguished by the presence of a tunnel and a valley landscape. We analyzed the changes in the wind according to the geometric conditions. Also, we analyzed the changes in the wind according to three different heights relative to the train. We also compared the wind produced by a KTX train and an SRT train. Finally, we used the results to derive the wind power energy harvested from the wind and discuss the expected utility.