• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.59-66
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• 2010

Around a toll plaza, vehicles do such maneuvers as slow down, stop, and speed up to pay their tolls when they use ordinary toll gates. They can be expected more fuel consumptions compared to the vehicles which use the Hi-pass, a Korean type of Electronic Toll Collection System(ETCS). To measure the exact amount of difference between the two gas consumptions, we equipped a test vehicle with a measurement system and constructed a model toll gate on our test field. Through the field tests on fuel consumptions, we could confirm a 36.7 % of energy saving when the test car used the Hi-pass. Then we projected the result on the total traffic volumes which had used national expressway network for five months from January 2009. Projected to the whole traffic, potential cost savings reached 5.34 billion won. We expect this result be frequently mentioned of to prove the fuel efficiency of the Hi-pass system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.23-35
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• 2009

This study proposes a methodology for estimating representative section travel times using individual vehicle travel information under the ubiquitous transportation environment (UTE). A novel approach is to substantialize a concept of dynamic node-links in processing trajectory data. Also, grouping vehicles was conducted to obtain more reliable travel times representing characteristics of individual vehicle travels. Since the UTE allows us to obtain higher accuracy of vehicle positions, travel times for each lane can be estimated based on the proposed methodology. Evaluation results show that less than 10% of mean absolute percentage error was achievable with 20% of probe vehicle rate. It is expected that outcome of this study is useful for providing more accurate and reliable traffic information services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.67-76
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• 2007

Although Hi-pass have been operated for alleviating traffic congestion and enhancing mobility in expressways since 2000, there is not any standard for safe operation. For that reason, we investigated about tubular markers, which is a typical facility for safety in Hi-pass. Tubular Markers are installed for separating same or opposite traffic flows spatially, supporting the marks at a place which has not only high possibility of accidents but distinguished carefulness of drivers. In this paper, it is noted two considerings; one is prevention of accident from the speed gap of autos and Hi-pass vehicles; the other is guarantee of necessary distance that Hi-pass vehicles could be changes the lanes for off-ramp. Focusing those considerations, it is proposed not only prefer distance of tubular markers, but also fundamental basic subjects. We anticipate that the results of this study would be useful reference in more safe and efficient tollgate operation of Hi-pass.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.48-54
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• 2018

With the 4th industry era, smart factories are emerging. In the era of multi-product small scale production, unmanned transportation vehicles are rapidly increasing in utilization of unmanned transportation vehicles that carry and arrange goods in the work space. The conventional unmanned vehicle detected its position by using the guided line method and the position based method for indoor location recognition and movement. This method has disadvantages of initial high cost and maintenance / maintenance. In this paper, to solve the disadvantages, the method of predicting the direct path of the unmanned vehicle through the Kalman filter is verified using the white LED marker of the warehouse and the position data and the image data of the white LED marker recognition image. Through this, the reliability of the linear movement which occupies the most part in the lattice structure is secured. It is also expected that the reliance on additional position sensors will also be reduced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.4
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• pp.52-61
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• 2015

PCE(Passenger Car Equivalents) is used to analysis of road capacity and LOS(Level of Service). In this study calculates PCE by number of lane and 12 vehicle type by MOLIT(Minister of Land, Infra Structure and Transport) using individual vehicle data. The results of the calculation, PCEs are increased when high vehicle classification level, many number of lanes and weekend. Heavy vehicle factors are smaller than KHCM on 4, 6 lane. Also, In this study estimates of PCE variation model by heavy vehicle percentage. Impact of Heavy vehicles on PCEs is the most sensitive on 2 lane. The results of the study, heavy vehicles low impact on PCE on multi-lane and business trips are a little in weekend.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.59-66
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• 2010

Korea have experienced a very rapid increase in police-reported collisions between bicycle and motor vehicles over the past decade. Even though cycling accidents are increasing, efforts to make urban areas more accomodating to cyclists are seldom formed. Clearance intervals(including both the yellow change and all-red clearance intervals) at signalized intersections that are of inadequate lengths for bicycles may cause accidents. Data on bicycling speed, acceleration and deceleration were tested and analyzed on the flat. Using the results of the analysis and based on the AASHTO's equation of the bicycle clearance interval, a methodology is got for calculation safe clearance intervals for bicycle riders. The clearance interval call for bicycles will be larger or same than for vehicles because of the speed, acceleration and deceleration difference. Adequate bicycle speed, acceleration and deceleration for korean bicycle users is presented in this paper. It is hoped that traffic engineers to provide safe intersection clearance time for bicycles use the results of this paper.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.47-52
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• 2011

Vehicle classification data are considerably used in the almost all fields of transportation planning and engineering. Highway agencies use a large number of vehicle classification schemes. Vehicles on the national highway are classified by 12-Category classification system, using number of axles, distances between axles, vehicle length, overhang, and other factors. In the case of using existing axle-sensor-based classification counters (that is, 12-category classification system), two-axle vehicles(Class 1 to 4) can be erroneously classified because a passenger vehicle becomes larger and similar with class 3 and 4. In this reason, this study proposes the vehicle classification scheme based on using vehicle height profiles obtained by a laser sensors. Also, the accuracy of the proposed method are tested through a field study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.70-80
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• 2012

In Vehicular Ad-hoc Network(VANET) which constructs networks without fixed infrastructure among vehicles, network topology is frequently changed due to high mobility. In case of urban model, communication disconnections caused by interruptions of communication propagation such as buildings and constructions could be often occurred. Therefore, in VANET environment a routing protocol to complement its characteristics is needed. This paper suggests an algorithm to improve the transmission performance at intersections by approaching of the distance-based broadcasting which utilizes the information of vehicle's position. By using relative velocity among vehicles, it makes the stability of route decision improved and reduces packet collisions through graded priorities in the intersection, and simultaneously improves the performance of data rate. It can be seen that the performance compared with previous algorithm is significantly improved when using the suggested algorithm in the urban traffic environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.82-96
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• 2020

The Demand Responsive Transit (DRT) system is the flexible public transport service that determines the route and schedule of the service vehicles according to users' requests. With increasing importance of public transport systems in urban areas, the development of stable and fast routing algorithms for DRT has become the goal of many researches over the past decades. In this study, a new heuristic method is proposed to generate fast and efficient routes for multiple vehicles using demand clustering and destination demand priority searching method considering the imbalance of users' origin and destination demands. The proposed algorithm is tested in various demand distribution scenarios including random, concentration and directed cases. The result shows that the proposed method reduce the drop of service ratio due to an increase in demand density and save computation time compared to other algorithms. In addition, compared to other clustering-based algorithms, the walking cost of the passengers is significantly reduced, but the detour time and in-vehicle travel time of the passenger is increased due to the detour burden.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.797-807
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• 2008

This paper proposes a new algorithm of extracting forward vehicle areas using the acquired lanes and road area information on road images with complex background to improve the efficiency of the vehicle detection. In the first stage, lanes are detected by taking into account the connectivity among the edges which are determined from a method of chain code. Once the lanes proceeding to the same direction with the running vehicle are detected, neighborhood roadways are found from the width and vanishing point of the acquired roadway of the running vehicle. And finally, vehicle areas, where forward vehicles are located on the road area including the center and neighborhood roadways, are extracted. Therefore, the proposed scheme of extracting forward vehicle area improves the rate of vehicle detection on the road images with complex background, and is highly efficient because of detecting vehicles within the confines of the acquired vehicle area. The superiority of the proposed algorithm is verified from experiments of the vehicle detection on road images with complex background.