• Title/Summary/Keyword: 주행패턴

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Recognition of Car Driving Patterns using a 3-Axis Accelerometer and Orientation Sensor (3축 가속도 센서와 방향센서를 이용한 운전패턴 인식)

  • Song, Chung-Won;Nam, Kwang-Woo;Lee, Chang-Woo
    • 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.

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Research on Domestic Driving Pattern for International Standardization of Light-duty Vehicles Emission Test Method (소형차 배출가스 시험방법 국제 표준화를 위한 국내 주행패턴 연구)

  • Choi, Kee-Choo;Park, Jun-Hong;Lee, Jong-Tae;Kim, Jeong-Soo;Lee, Kyu-Jin;Yi, Yong-Ju
    • Journal of Korean Society of Transportation
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    • v.30 no.1
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    • pp.31-43
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    • 2012
  • Domestic road type-and period-specific driving pattern measurement was required as Korea's participation in developing "Worldwide harmonized light-duty vehicle emission test procedure (WLTP/DHC)" studied by UN WP29. This study measured road driving data reflecting road and traffic conditions of Korea, and analyzed seven types of representative road type-and period-specific driving patterns with driving pattern standardization methodology proposed by WP29. PAMS (Portable Activity Monitoring Systems) equipment was used to collect enormous (35,410km) road driving data. There are significant difference among seven derived driving patterns.

A Research for Improvement of WIM System by Abnormal Driving Patterns Analysis (비정상 주행패턴 분석을 통한 WIM 시스템 개선 연구)

  • Park, Je-U;Kim, Young-Back;Chung, Kyung-Ho;Ahn, Kwang-Seon
    • Journal of Internet Computing and Services
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    • v.11 no.4
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    • pp.59-72
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    • 2010
  • WIM(Weigh-In-Motion) is the system measuring the weight of the vehicle with a high-speed. In the existing WIM system, vehicle weight is measured based on the constant speed and the error ratio has 10%. However, because of measuring the driving pattern, that is abnormal driving pattern which is like the acceleration and down-shift of the drivers, it has the error ratio which is bigger than the real. In order to it reduces the error ratio of WIM system, the improved WIM system needs to find the abnormal driving pattern. In order to reducing the error ratio of these WIM systems, the improved WIM system can find abnormal driving patterns. In this paper, the improved WIM system which analyzes the abnormality driving pattern influencing on the error ratio of WIM system of an existing and minimizes the error span is designed. The improved WIM system has the multi step loop structure of adding the loop sensor to an existing system. In addition, the measure function defined as an intrinsic is improved and the weight measured by the abnormal driving pattern is amended. The analysis of experiment result improved WIM system can know the fact that the error span reduces by 8% less than in the existing the maximum average sampling error 22.98%.

Driving Pattern Recognition System Using Smartphone sensor stream (스마트폰 센서스트림을 이용한 운전 패턴 인식 시스템)

  • Song, Chung-Won;Nam, Kwang-Woo;Lee, Chang-Woo
    • 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.

A Study on User Satisfaction Evaluation of Acceleration-Based Automated Driving Patterns (가속도 기반 자율주행 패턴에 대한 이용자 만족도 평가 연구)

  • Sooncheon Hwang;Dongmin Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.284-298
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    • 2023
  • With the rapid advances in automated driving technology, opportunities to experience automated driving directly or indirectly are being provided to the public. On the other hand, research on the preferred automated driving patterns from the user's perspective has not been conducted in Korea. This study used a driving simulator and an experimental vehicle capable of automated driving to evaluate the user satisfaction regarding longitudinal and lateral accelerations. Automated driving patterns were implemented in a virtual environment simulation using five values of longitudinal and lateral accelerations derived from driving experiments. Among these values, three were implemented through experimental vehicle-based automated driving to evaluate satisfaction and anxiety. The participants evaluated lateral acceleration more sensitively than longitudinal acceleration and showed higher levels of anxiety. Based on these results, the necessity of user-oriented evaluation research for automated driving patterns and the suitability of simulator-based evaluation methods were presented.

Development of a Workload Assessment Index Based on Analyzing Driving Patterns (운전자 주행패턴을 반영한 작업부하 평가지표 개발)

  • KIM, Yunjong;LEE, Seolyoung;CHOI, Saerona;OH, Cheol
    • Journal of Korean Society of Transportation
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    • v.35 no.6
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    • pp.545-556
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    • 2017
  • Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

A Study on ATO Control Pattern for Improving the Passenger's Comfort (승차감 향상을 위한 자동열차운전시의 제어패턴에 관한 연구)

  • 신한순;원충연
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.15 no.2
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    • pp.49-56
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    • 2001
  • This paper describes the improvement of passenger's comfort by analyzing the debasement of early adapted ATO control pattern. First we give the characteristics of ATO controller, principle of running control, distance & velocity calculation methods used mainly in INCHEON subway UNE 1 and then analyze the ATO control pattern. For early control pattern, we reviewed it in view of passenger's comfort while keeping the track conditions. In order to achieve the improvement of passenger's comfort we propose the modification of early ATO control pattern based on JERX characteristics. Simulation and application test are performed to prove the effectiveness of modified ATO control pattern.

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Modeling of the driving pattern for energy saving of the railway vehicles (철도차량의 주행에너지 절약을 위한 열차 주행 패턴 모델링)

  • Kim, Jung-Hyun;Kim, Sang-Hoon;Shin, Han-Chul;Lee, Se-Hoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2011.01a
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    • pp.107-108
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    • 2011
  • Since the development of railway technology, the current urban Railway the first train line in the country for safe operation control automatic/unattended operation, automatic train operation equipment available (ATO) on time and reliable operation has introduced. ATO Automatic operation controlled by the value (Target velocity) and the feedback value (Actual velocity) by the error between the backing and braking of the train by repeated low energy efficiency. In this paper, given a fixed distance stations between time operation with minimal energy in the driving characteristics and driving trains are modeled. Therefore, in line 5 real route time sectional drive straight sections for experimental data analysis / draft Section / curved and section of the train on that line is selected according to the changing driving patterns to minimize the energy optimal driving patterns were presented.

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Recognition of Multi-sensor based Car Driving Patterns for GeoVision (GeoVision을 위한 멀티 센서 기반 운전 패턴 인식)

  • Song, Chung-Won;Nam, Kwang-Woo;Lee, Chang-Woo
    • 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.

Development of a Methodology for Detecting Intentional Aggressive Driving Events Using Multi-agent Driving Simulations (Multi-agent 주행 시뮬레이션을 이용한 운전자 주행패턴을 반영한 공격운전 검지기법 개발)

  • KIM, Yunjong;OH, Cheol;CHOE, Byongho;CHOI, Saerona;KIM, Kiyong
    • 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.