• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.40-52
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• 2011

This paper develops a traffic condition decision algorithm to improve the reliability of traffic information on urban streets. This research is reestablished the criteria of qualitative traffic condition categorization and proposed a new qualitative traffic condition decision types and decision measures. The developed algorithm can be classified into 9 types for qualitative traffic condition in consideration of historical time series of speed changes and traffic patterns. The performance of the algorithm is verified through individual matching analysis using the radar detector data in Ansan city. The results of this paper is expected to help promotion of the traffic information processing system, real-time traffic flow monitoring and management, use of historical traffic information, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.34-44
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• 2007

Many urban cities deployed ITS technologies to improve the efficiency of traffic operation and management including a real-time franc control system (i.e., COSMOS). The system adopted loop detector system to collect traffic information such as volume, occupancy time, degree of saturation, and queue length. This paper investigated the applicability of detector information within COSMOS to represent the congestion level of the links. Initially, link travel times obtained from the field study were related with each of detector information. Results showed that queue length was highly correlated with link travel time, and direct link travel time estimation using the spot speed data produced high estimation error rates. From this analysis, a procedure was proposed to estimate congestion level of the links using both degree of saturation and queue length information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.59-71
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• 2018

This study was initiated to develop an optimal signal control algorithm for coordinated signalized intersections using individual vehicle's information which can be collected in a format of prove vehicle data (PVD) via V2I (Vehicle to Infrastructure) communication environment. For developing this signal optimization algorithm, three modules were developed for phase group length computation, split distribution, and phase sequence assignment. The simulation analysis using the microscopic simulation model, Vissim, was conducted for evaluating the effectiveness of the developed algorithm. The analysis result represented that the performance of the developed algorithm is far superior to that of the fixed coordinated signal control method which is the most common signal control method for coordinated signalized intersections in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.1 s.12
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• pp.1-12
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• 2007

The objective of Bus Information System developed as a part of the ITS, provides the operation information of buses to passengers and managers. The system uses roadside antennas (reading electronic tags on board buses) to enable wireless communication each other and radio data communication to deliver information about buses and their locations. This information is used to estimate the arrival time of the bus which will be shown on the bus stop message board or via internet. Bus Information System or Bus Management System (BMS) is going ahead and set up in many local governments, and recently quality improvement of the BIS is considered as a very important element in expanding of business or management. Therefore this research wished to contribute rationalization of the system by maintaining optimum quality. An gang was chosen to apply overall quality control process and will be evaluated in terns of its propriety and performance. This study has led the improvement of service and promote the use of public transits, which is the best way to solve the city traffic problem by effective management of public transits.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.25-33
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• 2014

This study investigates the reliability of DSRC-based traffic information system on the typical urban arterial with the minimum sample size method. VISSIM has been employed to calculate the required sample size. After comparing the number of hi-pass vehicles recorded from DSRC and the required sample size, this study found that the interrupted traffic state tends to generate more outliers than the uninterrupted one, the lack of the number of vehicles completely passing links with multiple driveways makes it difficult to estimate the reliable traffic information, the traffic information during peak hour is relatively more reliable than that during off-peak hour, and the reliability of DSRC-based traffic information system depends on the significance level in calculating the sample size. The driveway density and traffic signal operation due to the individual link length significantly affects the required sample size, resulting in determining the reliability of the DSRC-based traffic information system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.13-24
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• 2008

Real-time traffic data are readily obtainable by traffic surveillance systems of intelligent transportation systems (ITS). Such data greatly support further applications in the field of traffic operations, planning, and safety. However, traffic data should be appropriately processed to fully exploit the benefits of data collection capability. Rather than developing individual data processing techniques, which is major concern of existing studies, this study proposes a novel methodology for evaluating data processing techniques in an integrated manner. Also, a tool for implementing the proposed methodology is developed. Users can extract useful and more reliable traffic data based upon their ultimate purpose of data usage by the evaluation tool developed in this study. Actual freeway traffic data are, as an example, fed into the evaluation tool, and results are discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.55-64
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• 2003

This research is about executing the suitability evaluation of the data through wireless communication system in comparison with the data through the wire system used in National Highway Traffic Management System. The communication system for the evaluation was established on Peoyngteak-Anjung section(about 19 Km) at Route 38 in southern National Highway of the National Capital region where image detectors with the communication by wire were set up. In the situation, the comparison of the data transmission rates between the wire system and the proposed system was accomplished. Before we evaluate the possibility of application about the proposed system, the elements of wireless systems performed the spot investigations. Traffic data transmission test among the equipments was accomplished on the section of the Route 38 where wireless communication equipments were set up. And then, the test of traffic data transmission between the field equipment and the data collective center of wireless communication system was carried out. It evaluated the reliability of wireless communication data for the suitability evaluation of cable/wireless data collected while 73 days.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.493-498
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• 2017

Recently, traffic data is analyzed for efficiency of bus operation, D2D(: Door to Door) service, and self-driving of public transportation. However, various studies have been carried out to predict the delay time of public transportation, especially buses, but the research to date has been insufficient due to limitations of simple analysis and data acquisition. In this study, delay time estimation is performed by collecting and processing data such as day of the week, weather, and time of day based on bus operation information. The proposed method in this paper can be applied to autonomous public transport and public traffic control system by improving the accuracy by adding variables in the future.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.249-256
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• 2013

Recent days, the global warming problem due to excessive use of fossil fuels has been the world wide issue so that Korea government and developed countries make an alternative plan for eco-friendly and transportations by utilizing bicycles for health promotion. Existing Public Bicycle Rental Service Systems provide simple service such as bicycle rental management and tracking the location. However there is no user-side service for the information of the measure of carbon reduction, or use of bicycles. The proposed system in this paper provides users' health information, environmental information, personal information, counseling services and the measures of carbon reduction. The new system has been developed to carry out reducing carbon and growing green in terms of using bicycles by adopting Web 2.0 technology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.208-221
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• 2020

The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.