• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.161-170
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection. especially active shadows resulted from moving vehicles. In this paper a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98(%) in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic information concerning traffic flow is obtained to describe the load of each lane.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1479-1485
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• 2012

The development of a technique for the real-time sensing of a curve section is very important for active rolling-stocks in order to improve the curving performance. However, conventional methods using expensive track inspection equipment or various complex sensors are not practicable to be applied to commercial vehicles. Therefore, we have proposed a new method to estimate the curve radius of a curve section. This method uses the relative displacements occurring between the body and the bogie when the rolling-stock is running on a curve. To verify the validity of this method, we conducted a vehicle dynamics simulation and test using a real vehicle on a test line. The results confirmed the validity of the proposed method. We expect that this method will be effectively applied in studies of active rolling-stocks to increase the curving performance using active control technology.

• Journal of the Korean Society for Railway
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• v.9 no.5 s.36
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• pp.544-549
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• 2006

The characteristics of dynamic vibration are generally analyzed by an acceleration of a car body of high speed train and the acceleration can be applied to evaluation of running safety. The test of process and the analysis method about it are well explained on UIC Code 518 OR which is the spacial international standard about running safety and dynamic behavior on the line test for railway vehicle. Korean High Speed Train designed to operate at speed 350km/h has been tested on high speed line since it was developed in 2002 and it recorded the highest speed 352.4km/h at the 16th Dec. 2004 in Korea. This paper includes the analysis of running behavior of this train at speed 350km/h and the analysis of dynamic safety is presented in it, extending to the range of high speed while the UIC 518 limit the speed below 200km/h.

• Journal of the Korea Concrete Institute
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• v.22 no.6
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• pp.797-803
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• 2010

A dynamic analysis procedure is developed to provide a better estimation of the dynamic responses of pre-stressed concrete (PSC) box girder bridges on the Korea high speed railway. Particularly, a three dimensional numerical model including the structural interaction between high speed vehicles, bridges and railway endures to analyze accurately and evaluate with in-depth parametric studies for dynamic responses of bridge due to the high speed railway vehicles. Three dimensional frame element is used to model the PSC box girder bridges, simply supported span lengths 40 m. The high-speed railway vehicles (K-TGV) including a locomotive are used as 38-degree of freedom system. Three displacements (vertical, lateral, and longitudinal) as well as three rotational components (pitching, rolling, and yawing) are considered in the 38-degree of freedom model. The dynamic analysis by Runge-Kutta method which are able to analyze considering the dynamic impact factors are compared and contrasted. It is proposed as an empirical formula that the impact factors damaged the bridge load-carrying capacities occurs to the bride due to high-speed vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.610-630
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• 2020

A large number of people suffered from traffic accidents each year, so people pay more attention to traffic safety. However, the traditional methods use laser sensors to calculate the vehicle distance at a very high cost. In this paper, we propose a method based on deep learning to calculate the vehicle distance with a monocular camera. Our method is inexpensive and quite convenient to deploy on the mobile platforms. This paper makes two contributions. First, based on Light-Head RCNN, we propose a new vehicle detection framework called Light-Car Detection which can be used on the mobile platforms. Second, the planar homography of projective geometry is used to calculate the distance between the camera and the vehicles ahead. The results show that our detection system achieves 13FPS detection speed and 60.0% mAP on the Adreno 530 GPU of Samsung Galaxy S7, while only requires 7.1MB of storage space. Compared with the methods existed, the proposed method achieves a better performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.59-72
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• 2017

As the part of study which handles the measure to use the individual vehicle information of taxi GPS data on signal controls in order to overcome the limitation of Loop detector-based collecting methods of real-time signal control system, this paper conducted series of evaluations and improvements on link travel time, queue vehicle time estimates and traffic condition decision algorithm from the research introduced in 2016. considering the control group and the other, the link travel time has enhanced the travel time and the length of queue vehicle has enhanced the estimated model taking account of the traffic situation. It is analyzed that the accuracy of the average link travel time and the length of queue vehicle are respectably both approximately 95 % and 85%. The traffic condition decision algorithm reflected the improved travel speed and vehicle length. Smoothing was performed to determine the trend of the traffic situation and reduce the fluctuation of the data, and the algorithms have refined so as to reflect the pass period on overflow judgment criterion.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.310-318
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• 2004

In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.2 s.7
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• pp.13-22
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• 2005

The purpose of this research is how to estimate the traffic queue length in the signal intersection accurately. The current traffic queue length algorithm in COSMOS has been using the congestion diagram which comes from the speed of an average separated vehicle - using average vehicle length and the occupancy time from loop detectors. So some errors were occurred by the speed estimation method using average vehicle lengths. And Operators had been difficult to optimize some variables for measuring the traffic queue length estimation algorithm in COSMOS. Therefore the traffic queue length estimation algorithm on the basis of the relation between distances and occupancy rates from loop detectors was developed in this thesis. This thesis had the advantage of using occupancy rates which came out from loop detectors easily and no need to optimize some variables for the established algorithm in COSMOS. And the results of testing this algorithm in some sites which had installed COSMOS system showed better results than COSMOS system's results. But it was noted that further studies which carry it out in various sites and under various cases are necessary for applying to actual intersections.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.15-23
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• 2016

To support the telematics and infotainment services, vehicle-to-everything (V2X) communication requires a robust and reliable network. To do this, the 3rd Generation Partnership Project (3GPP) has recently developed V2X communication. For reliable communication, accurate channel estimation should be done. However, because vehicle speed is very fast, radio channel is rapidly changed with time. Therefore, it is difficult to accurately estimate the channel. In this paper, we propose the new linear minimum mean square error (LMMSE) channel interpolation scheme based on the Long Term Evolution (LTE) sidelink system in vehicle-to-vehicle (V2V) environments. In our proposed reduced decision error (RDE) channel estimation scheme, LMMSE channel estimation is applied in the pilot symbol, and then in the data symbol, smoothing and LMMSE channel interpolation scheme is applied. After that, time and frequency domain averaging are applied to obtain the whole channel frequency response. In addition, the LMMSE equalizer of the receiver side can reduce the error propagation due to the decision error. Therefore, it is possible to detect the reliable data. Analysis and simulation results demonstrate that the proposed scheme outperforms currently conventional schemes in normalized mean square error (NMSE) and bit error rate (BER).

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.3-9
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• 2017

Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).