• Title/Summary/Keyword: Driving pattern

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Driving Pattern Recognition Algorithm using Neural Network for Vehicle Driving Control (차량 주행제어를 위한 신경회로망을 사용한 주행패턴 인식 알고리즘)

  • Jeon, Soon-Il;Cho, Sung-Tae;Park, Jin-Ho;Park, Yeong-Il;Lee, Jang-Moo
    • Proceedings of the KSME Conference
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    • 2000.04a
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    • pp.505-510
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    • 2000
  • Vehicle performances such as fuel consumption and catalyst-out emissions are affected by a driving pattern, which is defined as a driving cycle with the grade in this study. We developed an algorithm to recognize a current driving pattern by using a neural network. And this algorithm can be used in adapting the driving control strategy to the recognized driving pattern. First, we classified the general driving patterns into 6 representative driving patterns, which are composed of 3 urban driving patterns, 2 suburban driving patterns and 1 expressway driving pattern. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, relative duration spent at stop, average acceleration and average grade are chosen to characterize the driving patterns. Second, we used a neural network (especially the Hamming network) to decide which representative driving pattern is closest to the current driving pattern by comparing the inner products between them. And before calculating inner product, each element of the current and representative driving patterns is transformed into 1 and -1 array as to 4 levels. In the end, we simulated the driving pattern recognition algorithm in a temporary pattern composed of 6 representative driving patterns and, verified the reliable recognition performance.

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A Study of Fuel Reduction Driving Pattern on Diesel Locomotives (연료절감운전 패턴 연구)

  • Son, Kyoung-So;Kim, Dae-Sik;Kim, Ho-Soon;Kim, Teak-Sung;Park, Tae-Gi
    • Proceedings of the KSR Conference
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    • 2011.10a
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    • pp.1405-1411
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    • 2011
  • It is very often for the experienced diesel locomotive drivers to identify the proper replacing time for the fuel adjustment tube only based on their experience. Because of that, sometimes the locomotive's fuel is burned out due to the unnecessary torque. Or sometimes, the locomotive does not operate with its accelerating performance because the fuel is not supplied at the appropriate moment. Meanwhile, recent typical auto vehicles provide drivers with the average fuel efficiency and the instant fuel efficiency in real-time. By providing the real time display mentioned above, it is one of the good examples that those drivers, who had driven their cars not properly and used a lot of fuel with their bad driving habits, obtain the efficient driving pattern by continuous educating effect. Similarly, if the diesel locomotive provides the train driver with the optimal driving pattern within a certain driving section, it will be effective for fuel saving. It is possible to make the most effective driving pattern by performing the repeated trial running especially for the railway because the track's operating routes, its grades, and etc are relatively precise. This research analyzes the result data which was obtained by many times trial running on the identical section after equipping the fuel use measuring device to a certain test vehicle, and confirms the fuel saving effect depending on the driving pattern along the test section. At the same time, the research to establish the optimal driving pattern was progressed.

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ECO Driving Patterns Derived from the Analysis of the Problems of the Current Driving Pattern of Electric Multiple Unit in ATO System (현행 ATO 시스템 전동차 운행패턴의 문제점 분석을 통한 ECO 운행패턴 도출방안 연구)

  • Kim, Kyujoong;Lee, Keunoh;Kim, Juyong
    • Journal of the Korean Society of Safety
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    • v.28 no.3
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    • pp.23-28
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    • 2013
  • This study focuses on finding ways to derive train's optimal ECO driving pattern, which can improve the ride quality and reduce driving energy consumption with keeping the time interval between the stations. As research method, we compared difference of currently operating train's ATO and MCS driving patterns, and concentrated upon the things need to consider in simulation in order to improve the existing pattern of ATO driving pattern's issues with securing the train operation safety. Determining driving pattern minimizing energy consumption by controlling powering within speed limit and controlling switching to coasting at appropriate point considering the track conditions for each section, and determining braking control starting time considering ride comfort and precise stopping is considered to be most important.

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 Application of ECO Driving Pattern of Electric Multiple Unit in ATO System (Focus on Simulation Results) (ATO 시스템 전동차의 ECO 운행패턴 적용에 관한 연구 (시뮬레이션 결과를 중심으로))

  • Kim, Kyujoong;Lee, Keunoh;Kim, Juyong
    • Journal of the Korean Society of Safety
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    • v.28 no.2
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    • pp.6-13
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    • 2013
  • This study focuses on finding ECO driving patterns which consider driving safety of the ATO system train and reliability and which optimize efficiency of the driving energy consumption. Research results derived by performing simulation of those 5 models show that the emergency braking which affects safety of passenger and the machinery is minimized, and safe driving speed is maintained by the prohibition of drastic acceleration/deceleration, coasting and constant-speed driving. Therefore if this result is applied to the urban railway train by amending or making ATO program to save energy usage that improve environmental quality, its effects as ECO driving pattern is huge.

A Study on In-vehicle Aggressive Driving Detection Recorder System for Monitoring on Drivers' Behavior (운전행태 감시를 위한 차량 위험운전 검지장치 연구)

  • Hong, Seung-Jun;Lim, Lyang-Keun;Oh, Ju-Taek
    • Transactions of the Korean Society of Automotive Engineers
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    • v.19 no.3
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    • pp.16-22
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    • 2011
  • This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

Development of a Vehicle Driving Cycle in a Military Operational Area Based on the Driving Pattern (군 운용 지역에서 차량의 주행 패턴에 따른 주행모드 개발)

  • Choi, Nak-Won;Han, Dong-Sik;Cho, Seung-Wan;Cho, Sung-Lai;Yang, Jin-Saeng;Kim, Kwang-Suk;Chang, Young-June;Jeon, Chung-Hwan
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.4
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    • pp.60-67
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    • 2012
  • Most of a driving cycle is used to measure fuel consumption (FC) and emissions for a specified vehicle. A driving cycle was reflected geography and traffic characteristics for each country, also, driving pattern is affected these parameters such as vehicle dynamics, FC and emissions. Therefore, this study is an attempt to develop a driving cycle for military operational area. The proposed methodology the driving cycle using micro-trips extracted from real-world data. The methodology is that the driving cycle is constructed considering important parameters to be affected FC. Therefore, this approach is expected to be a better representation of heterogeneous traffic behavior. The driving cycle for the military operational area is constructed using the proposed methodology and is compared with real-world driving data. The running time and total distance of the final cycle is 1461 s, 13.10 km. The average velocity is 32.25 km/h and average grade is 0.43%. The Fuel economy in the final cycle is 5.93 km/l, as opposed to 6.10 km/l for real-world driving. There were about 3% differences in driving pattern between the final driving cycle and real-world driving.

Characteristics of Fuel Economy and CO2 according to Driving Pattern of Drivers (운전자간 드라이빙 패턴에 따른 연비·온실가스 특성)

  • Kang, Minkyung;Kwon, Seokjoo;Seo, Youngho
    • Journal of Institute of Convergence Technology
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    • v.6 no.1
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    • pp.13-16
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    • 2016
  • The purpose of this study is analysing the characteristics of vehicle fuel economy and greenhouse gase emissions according to driving pattern of drivers. Current fuel economy has not established on official test methods. The difference between actual fuel efficiency and specification fuel efficiency bring up consumer complaints and misunderstandings about fuel economy. Against this background, The country is progressing the study on influence of the fuel efficiency according to variety test conditions. This study analyze the driving pattern of the different drivers and influence of the fuel efficiency according to driving pattern of different drivers.

A Study on the Estimation of Vehicle Driving Pattern and Cold Emission Length by using on-board Telematics Devices (텔레매틱스 기술을 이용한 자동차 주행 패턴 및 냉간 배출거리 평가에 관한 연구)

  • Choi, Sang-Jin;Kim, Pil-Su;Park, Sung-Kyu;Park, Gun-Jin;Kim, Jin-Yun;Hong, Young-Sil;Jang, Young-Kee;Kim, Jeong;Kim, Jeong-Soo
    • Journal of Korean Society for Atmospheric Environment
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    • v.29 no.6
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    • pp.734-744
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    • 2013
  • In this study, the telematics device was installed on the car (OBD-II) to collect the information on the operation conditions from each sample vehicle. Based on the information the domestic driving pattern was analysed and the ratio of cold start length was estimated. As a result of analysis for driving pattern, we found a difference in the frequency of driving on the hourly or seasonal basis. Then, the driving pattern of the rush hours, weekdays, and weekends could be derived. Also, from the study, an average of 2.22 times per day occurred in a single trip and average driving distance for the trip was 15.72 km. In addition, the proportion of cold start length was analyzed to be 16.11%. The seasonal cold start length has big difference from season to season (Winter 26.63%, Summer 8.22%, Intermediate 12.65%). There was an inverse relationship between the outside temperature and ratio of cold start length. In order to improve the accuracy of the cold emission estimation, it is necessary to apply domestic ratio of cold start length that driving pattern and temperature in Korea is reflected.

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%.