• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.22-32
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• 2002

This paper describes about non-burial AVI (Automatic Vehicle Identification) system using general vehicle as probe car for obtaining more accurate traffic information while conserving road pavement surface. Existing spot traffic detectors have their own limits of not obtaining right information owing to its mathematical method. Burial AVI systems have some defects, causing traffic jam, needing much maintenance cost because of frequent cutting of loop and piezo-electric sensors. Especially, they have hard time to make right detection, when it comes to jamming time. Therefore, in this paper, we propose non-burial AVI system with laser trigger unit. Proposed non-burial AVI system is developed to obtain regional traffic information from normal Passing vehicle by automatic license number recognition technology. We have adapted it to national highway section between Suwon city and Pyong$\~$Taek city(9.5km) and get affirmative results. Vehicle detection rate of laser trigger unit is more than 95$\%$, vehicle recognition rate is 87.8$\%$ and vehicle matching rate is about 14.3$\%$. So we regard these as satisfying results to use the system for traffic information service. We evaluate proposed AVI system by regulation of some institutions which are using similar AVI system and the proposed system satisfies all conditions. For future study, we have plan of detailed research about proper lane number from all of the target lanes, optimal section length, information service period, and data fusion method for existing spot detector.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.183-194
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• 2001

The centralized traffic information system is to gather and analyze real-time traffic information, to receive traffic information request from user, and to send user processed traffic information such as a path finding. Position information, result of destination search, and other information. In the centralized traffic information system, a server received path-finding requests from many clients and must process clients requests in time. The algorithm of multiple path-finding is needed for a server to process clients request, effectively in time. For this reason, this paper presents a heuristic algorithm that decreases time to compute path-finding requests. This heuristic algorithm uses results of the neighbor nodes shortest path-finding that are computed periodically. Path-finding results of this multiple path finding algorithm to use results of neighbor nodes shortest path-finding are the same as a real optimal path in many cases, and are a little different from results of a real optimal path in non-optimal path. This algorithm is efficiently applied to the general topology and the hierarchical topology such as traffic network. The computation time of a path-finding request that uses results of a neighbor nodes shortest path-finding is 50 times faster than other algorithms such as one-to-one label-setting and label-correcting algorithms. Especially in non-optimal path, the average error rate is under 0.1 percent.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.11-20
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• 2014

Due to the importance of vehicle detector which plays an essential role in generating real-life traffic information, maintaining detector data quality is preeminent in advanced traffic management and information systems (ATMIS). To this end, agencies periodically conduct performance tests on detectors. Detector evaluation is generally performed by comparing baseline data with corresponding detector data. Here, two important things need to be addressed; one is errors (or uncertainties) included in baseline data and the other is the confidence interval concept to represent evaluation results of sample data to corresponding ones of population. To resolve these problems, a new detector evaluation scheme is introduced and the scheme is applied to individual level detector evaluations of loop, video image, and radar detectors. The purpose of individual level evaluation is to eliminate the balancing (or cancelling-out) effects of over- and under-counts. As a consequence, the proposed scheme is proven to be effectively applied to real-world detector evaluations.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.117-122
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• 2022

In this paper, we developed a vehicle control terminal using IoT and low-power long-distance communication (NB-IoT) technology. This system collects information on the location and status of a parked vehicle, and transmits the vehicle status to the vehicle owner's terminal in real time with low power to prevent vehicle theft, and in the case of a vehicle in motion, When primary information about the vehicle, such as an impact, is collected and transmitted to the server, the server analyzes the relevant data to generate secondary information on traffic congestion, road damage, and safety accidents. By sending it, you can know the exact arrival time of the vehicle at its destination. This terminal device is an IoT gateway for a vehicle and can be connected to various wired and wireless sensors inside the vehicle. In addition, the data collected from vehicle maintenance, efficient operation, and vehicles can be usefully used in the private or public sector.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.90-101
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• 2016

This study was initiated to develop an algorithm for traffic condition adaptive optimal traffic signal control for isolated intersections based on the vehicle trajectory data. The algorithm determines the optimal cycle length, phase lengths, phase sequences using the data collected under V2X communication environment every second. In addition, the algorithm utilizes a traditional feature of the actuated signal control, gap-out, using traditional detector systems to consider the mixture of normal vehicles and vehicles equipped with the V2X communication function. The performance of the algorithm was compared with that of the fixed signal timing plan which was optimized with Synchro under a microscopic traffic simulation-based test bed. As a result, the overall performance, including average delay, average stop delay, the number of stops, and average speed, are improved apparently. In addition, the amount of improvement get bigger as the traffic volume in the intersection as well as the number of vehicles equipped with the V2X communication function increase.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.213-221
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• 2014

Since 2005, when "The Mobility Enhancement for the Mobility Impaired Act" was enacted, special transport systems(SPS) has been introduced by each responsible local entity. For its efficient operations and service enhancements, a clear understanding of travel patterns of SPS users is required. Yet we currently have a very limited understanding about them due to a lack of necessary data. This study represents an attempt to provide a better understanding of SPS user's travel patterns with the data generated by Gyeongsangnam-do SPS Call Center. The data include the number, time and day of calls, origins and destinations of callers, types of callers' impairement etc. The data thus allow one to analyze users' travel patterns, including area-wide O-D patterns. There were a number of interesting findings. For example, wheelchair users are only about 42% and the trips are made mostly on non-peak daytime periods. The results are expected to provide a helpful information not just for Center's SPS operations, but for other local entities that are interested in developing similar call centers as well. By refining the SPS system, periodic patterns of callers could be identified in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.42-58
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• 2008

Nowadays the installation of Real-time Traffic Signal Control system is gradually spread, in order to solve the traffic problem which become serious. The most important thing are reliability of data collection and functionality of system in Real-time Traffic Signal Control System. But, the evaluation for those introduction system are defective after system constructing. So, many systems are not working properly to those systems's primarily purpose. This study is executed expansion through field test and analysis which check performance and advise of system operation. It has purpose to establish of the maintenance system of Real-time Traffic Signal Control system. As the result of analysis, we could find the several problems in this study. So, we also could guess that the effective maintenance systems of the Real-time Traffic Signal Control system is necessary within few years.