• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.7-10
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• 2012

본 논문에서는 스마트폰을 이용하여 도로 주행 정보를 기록하고 운전자에게 패턴 별 주행정보를 제공하는 라이프로그(Lifelog) 형태의 서비스에 목적을 두고 있다. 운전자의 도로 주행 데이터를 데이터베이스화한 이 정보는 다양하게 이용될 수 있다. 주행 패턴 인식은 이벤트 구간 검출 과정을 통한 패턴 구간을 검출하고 가속도 센서와 방향 센서, 즉 멀티 센서 기반으로 주행패턴을 인식한다. 주행 패턴을 분석 후 시간 정보를 이용하여 촬영된 영상 데이터에서의 패턴 구간 영상을 같이 제공한다. 이렇게 패턴 구간의 센서 스트리밍 정보와 영상을 제공하면 운전자의 운전 성향 및 주행 기록을 분석하는데 이용될 수 있다. 따라서 주행패턴 인식 알고리즘을 프로토타입으로 제안한다.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2002.05a
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• pp.241-250
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• 2002

본 연구의 목적은 최근 운전자 행동에 대한 연구 방법으로 매우 중요하게 대두되고 있는 운전 시뮬레이션 방법을 이용하여 운전자들이 보이는 기본적인 운전 수행 능력 및 이러한 운전 수행 능력과 관련이 가장 깊은 것으로 기존의 연구들이 밝혀왔던 기본적인 지각적/인지적/운동적 수행 능력을 측정하여 운전자 수행을 평가하는 것을 목적으로 한다. 특히 운전자의 운전 수행 및 운전과 관련된 기본적인 정신/운동 수행 능력은 정보 처리적 관점에서 측정되고 분석되었으며, 이를 통해 운전자들이 보이는 기본적인 정보처리 능력의 패턴에 대한 전반적 이해를 시도하였다. 본 연구에서는 기본적인 운전 수행 능력을 평가하는데 사용되는 차량의 속도 유지와 차선 유지에 대한 측정치와 더불어 운전과 관련한 인간 수행 중에서 단순 반응 능력, 선택 반응 능력, 속도 추정 능력, 청각적 주의나 시각적 주의의 분산 능력 등이 운전 시뮬레이션을 통하여 운전 중에 실시간으로 측정되었다. 본 연구에서 수집된 자료는 운전자들의 실제 운전 수행 및 이와 관련된 정보 처리 활동에 대한 표준화된 준거를 제시하는데 기초적 자료로 사용될 수 있으리라 생각된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.709-714
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• 2001

Recently, most vehicles has the Automatic transmission system as their transmission system. The automatic transmission system operates with fixed shift patterns. In the opposite of manual operation, it is easy and convenient for driving. Though these merit, the system can not evaluate the driver s intension because of usage of fixed shift pattern. To consider driver s intension, we must consider both the driving intensity of driver and the status of vehicle. In this paper, we developed flexible automatic transmission system by using the proposed moduled neural networks which can learn the status of th vehicle and driver s intensity. As a results, we compare the transmission system using fixed shift pattern and the proposed transmission system and show the good performance in the change of shift position.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.55-60
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• 2004

Most vehicles having automatic transmission system use fixed standard shift map to provide automatic transmission for driver. In this case, driver who operates vehicle may be complaint with the fixed transmission pattern being different from the driver's intention. In this paper, therefore, to infer the driver's intention module for learning the driver's intention with related input variables using soft computing method is proposed. After inference, the standard shift map will be shifted according to a certain parameter decided from the proposed module for providing proper shift pattern. The efficiency of the proposed module is evaluated by the data acquired from real time driving.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.579-586
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• 2014

This paper analyzes the recognition of driver's behavior in lane change using context-free grammar. In contrast to conventional pattern recognition techniques, context-free grammars are capable of describing features effectively that are not easily represented by finite symbols. Instead of coordinate data processing that should handle features in multiple concurrent events respectively, effective syntactic analysis was applied for patterning of symbolic sequence. The findings proposed the effective and intuitive method for drivers and researchers in driving safety field. Probabilistic parsing for the improving this research will be the future work to achieve a robust recognition.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.35-42
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• 2012

The database for driving patterns can be utilized in various system such as automatic driving system, driver safety system, and it can be helpful to monitor driving style. Therefore, we propose a driving pattern recognition system in which the sensor streams from a smartphone are recorded and used for recognizing driving events. In this paper we focus on the driving pattern recognition that is an essential and preliminary step of driving style recognition. We divide input sensor streams into 7 driving patterns such as, Left-turn(L), U-turn(U), Right-turn(R), Rapid-Braking(RB), Quick-Start(QS), Rapid-Acceleration (RA), Speed-Bump(SB). To classify driving patterns, first, a preprocessing step for data smoothing is followed by an event detection step. Last the detected events are classified by DTW(Dynamic Time Warping) algorithm. For assisting drivers we provide the classified pattern with the corresponding video stream which is recorded with its sensor stream. The proposed system will play an essential role in the safety driving system or driving monitoring system.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1185-1187
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• 2011

이 논문에서는 운전자의 운전 패턴을 분석하기 위한 멀티 센서 기반의 패턴 분석 알고리즘을 제안한다. 센서를 통해 얻어진 주행 데이터의 상관 관계를 비교, 분석하여 주행 패턴을 인식한다. 가속도 센서에 작용하는 중력값과 지자기 센서의 방향 데이터을 통해 각 운전 패턴을 인식하는 정확도를 높이는데 이용하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.30-35
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• 2005

An automatic transmission pattern with the fixed standard shift map can provide comfortable shift to driver. However it may be a complain to provide shift by the same shift pattern for driver because the inclination of a driver may be various. Therefore, in this paper, we design the decision module, which can decide the driving style using input to decide the inclination of the driver and driving manner. The goal of this paper is to calibrate the shift map according to the inclination of the driver using the decided driving manner from the proposed module. As a result, the proposed intelligent automatic transmission system can provide a suitable shift point and time to the driver. To verify the performance of the proposed system, the real data that is obtained from the road test will be used.

• Korean Journal of Culture and Social Issue
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• v.22 no.1
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• pp.19-39
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• 2016

Though research has shown that public transportation drivers experience greater burnout than other drivers, the sources of their burnout and possible mediators remain largely unknown. In response, in this study we investigate the relationships among sensation seeking, Type A driving behavior, and meaning of work to elucidate the burnout experienced by bus drivers in Gyeonggi-do, South Korea. To collect data regarding these relationships, 188 bus drivers answered a questionnaire involving the sensation seeking scale, burnout scale, and meaning of work scale. Results showed that Type A driving behavior mediated the relationship between sensation seeking and burnout, while meaning of work moderated the mediated model. These findings demonstrate that sensation-seeking bus drivers tend to experience greater burnout given their tendency to exhibit Type A driving behavior, and this relationship depends on perceived meaning of work. This study therefore contributes meaningful information and outlines significant implications in understanding drivers' burnout.