• Title/Summary/Keyword: 윤거

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Development of wheel width and tread acquisition algorithm using non-contact treadle sensor (무접점 답판 센서를 사용한 차량 바퀴의 윤폭 / 윤거 획득 알고리즘 개발)

  • Seo, Yeon-Gon;Lew, Chang-Guk;Lee, Bae-Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.6
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    • pp.627-634
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    • 2016
  • Vehicle classification system in domestic tollgates is usually to use treadle sensor for calculating wheel width and tread of the vehicle. due to the impact that occurs when the wheels of the vehicle contact, treadle sensor requires high durability. recently, KHC(Korea Highway Corporation) began operating high-speed lane for cargo truck. high-speed cargo truck generate more impact the design criteria of previous treadle. therefore, an increase in the maintenance and management costs of the treadle damage is concerned. In this paper, we propose an algorithm for obtaining optimal wheel width and tread using non-contact treadle sensor that been improved durability from physical impacts. for the verification of the proposed algorithm, a field test was performed using 1/2/3/6 class vehicles based on the KHC's classification criteria. through this experiments, maximum error of the width and the tread is each ${\pm}2cm$ and ${\pm}8cm$, also the accuracy was measured as 98%, 97% or more, and proved that the proposed algorithm valid on to apply to the vehicle classification system.

Development of Vehicle Classification Algorithm using Non-Contact Treadle Sensor for Toll Collect System (통행료징수시스템을 위한 무접점 답판 방식의 차종분류 알고리즘 개발)

  • Seo, Yeon-Gon;Lew, Chang-Guk;Lee, Bae-Ho
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.12
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    • pp.1237-1244
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    • 2016
  • Vehicle classification system in domestic tollgates is usually to use treadle sensor for calculating wheel width and tread of the vehicle. Due to the impact that occurs when the wheels of the vehicle contact, treadle sensor requires high durability. Recently, KHC(Korea Highway Corporation) began operating high-speed lane for cargo truck. High-speed cargo truck generate more impact the design criteria of previous treadle. Therefore, an increase in the maintenance and management costs of the treadle damage is concerned. In this paper, we propose an algorithm to classify vehicles using non-contact treadle sensors for improving durability from physical impacts. This was based on the KHC's classification criteria and showed a classification accuracy of 99.5 % in one experiment with 1892 vehicles through Changwon tollgate in 1020 local road. Therefore, it shows that vehicle classification system using non-contact treadle sensor could be applied to domestic toll tollgates, effectively.

Developing a method to estimate vehicle speeds in a low-cost vehicle detector with an inclined sensor (사선형 센서를 이용한 저가 검지장비의 차량속도 추정방법 개발)

  • Kim, Hyoung-Soo;Oh, Ju-Sam
    • International Journal of Highway Engineering
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    • v.11 no.1
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    • pp.59-67
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    • 2009
  • With the development of high-cost vehicle detectors, low-cost detectors have also been studied due to the advantage that more detectors are provided within limited budgets. This study proposed a method to estimate vehicle speeds using vehicles' track data from auto manufacturers and time stamps obtained when vehicles' tires pass an inclined sensor (here, a tape switch sensor). In speed estimation, small vehicles and large vehicles is distinguished according to the ratio of time stamps for a wheelbase and a rear track obtained from a tape switch sensor. In particular, speed estimation can be adjusted through a parameter to determine vehicles' size so as to take into account location properties such as vehicles' classification ratio. The low-cost vehicle detector with an inclined sensor proposed in this study is expected to be widely utilized to monitor traffic conditions thanks to low cost.

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Effects of Tread, Wheelbase and Axle Load Distribution on Tractor Vibrations (윤거, 축거, 차축 하중 분포가 트랙터 진동에 미치는 영향)

  • 조춘환;김경욱
    • Journal of Biosystems Engineering
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    • v.21 no.3
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    • pp.293-305
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    • 1996
  • Effects on the tractor vibrations of tread, wheelbase and axle load distribution were analyzed by using mathematical models of tractor and random road surface. A 4 degrees of freedom tractor model was developed to predict the bounce, pitch and roll motions of tractor. The front axle which is constrained to roll with respect to tractor body was also included in the model. A random road profile was generated and used as an excitation input to the tractor. Output vibrations of the model were predicted and analyzed by a computer simulation method. In general, longer tread tends to reduce rolling and longer wheelbase does bouncing and pitching motions. Tractor vibrations were minimum when the ratio of front to rear axle loads was in the range of 30:70-35:65. Sensitivity analysis showed that rolling and pitching motions most sensitively varied with changes in tread and wheelbase while bouncing motion did with the location of mass center.

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New Vehicle Classification Algorithm with Wandering Sensor (원더링 센서를 이용한 차종분류기법 개발)

  • Gwon, Sun-Min;Seo, Yeong-Chan
    • Journal of Korean Society of Transportation
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    • v.27 no.6
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    • pp.79-88
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    • 2009
  • The objective of this study is to develop the new vehicle classification algorithm and minimize classification errors. The existing vehicle classification algorithm collects data from loop and piezo sensors according to the specification("Vehicle classification guide for traffic volume survey" 2006) given by the Ministry of Land, Transport and Maritime Affairs. The new vehicle classification system collects the vehicle length, distance between axles, axle type, wheel-base and tire type to minimize classification error. The main difference of new system is the "Wandering" sensor which is capable of measuring the wheel-base and tire type(single or dual). The wandering sensor obtains the wheel-base and tire type by detecting both left and right tire imprint. Verification tests were completed with the total traffic volume of 762,420 vehicles in a month for the new vehicle classification algorithm. Among them, 47 vehicles(0.006%) were not classified within 12 vehicle types. This results proves very high level of classification accuracy for the new system. Using the new vehicle classification algorithm will improve the accuracy and it can be broadly applicable to the road planning, design, and management. It can also upgrade the level of traffic research for the road and transportation infrastructure.

Determining the Appropriate Installation Angle of Skewed Sensor to Measure Vehicle Wandering (차량 원더링 계측을 위한 사선센서 적정 설치각도 결정)

  • Oh, Ju-Sam;Jang, Kyung-Chan;Kim, Min-Sung;Jang, Jin-Hwan
    • International Journal of Highway Engineering
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    • v.10 no.3
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    • pp.79-86
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    • 2008
  • This paper proposed the appropriate installation angle of skewed sensors for measuring vehicle wandering data, which are collected to figure out the location of dynamic weight of a moving vehicle on roadways. We developed a device using tape-switch sensors and a computer program and collected vehicle wandering data with the device and probe vehicles. As a result, the steeper the skewed sensor was installed, the lower the error was shown. However, we could not collect proper data when a skewed sensor was set up higher than $30^{\circ}$ due to tandem axle. Therefore, this study suggested the appropriate angle of skewed sensors as a degree of $20^{\circ}$ to $25^{\circ}$ for gathering wandering data.

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Estimation of Individual Vehicle Speed Using Single Sensor Configurations (단일 센서(Single Sensor)를 활용한 차량속도 추정에 관한 연구)

  • Oh, Ju-Sam;Kim, Jong-Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.461-467
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    • 2006
  • To detect individual vehicular speed, double loop detection technique has been widely used. This paper investigates four methodologies to measure individual speed using only a single loop sensor in a traveling lane. Two methods developed earlier include estimating the speed by means of (Case 1) the slop of inductance wave form generated by the sensor and (Case 2) the average vehicle lengths. Two other methods are newly developed through this study, which are estimations by measuring (Case 3) the mean of wheelbases using the sensor installed traversal to the traveling lane and (Case 4) the mean of wheel tracks by the sensor installed diagonally to the traveling lane. These four methodologies were field-tested and their accuracy of speed output was compared statistically. This study used Equality Coefficient and Mean Absolute Percentage Error for the assessment. It was found that the method (Case 1) was best accurate, followed by method (Case 4), (Case 2), and (Case 3).

Development and Application of the High Speed Weigh-in-motion for Overweight Enforcement (고속축하중측정시스템 개발과 과적단속시스템 적용방안 연구)

  • Kwon, Soon-Min;Suh, Young-Chan
    • International Journal of Highway Engineering
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    • v.11 no.4
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    • pp.69-78
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    • 2009
  • Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.

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