• Journal of Korea Spatial Information System Society
• /
• v.10 no.3
• /
• pp.55-65
• /
• 2008

For obtaining telematics traffic information(travel time or speed in an individual link), there are many kinds of devices to collect traffic data. Since the GPS satellite signals have been released to civil society, thank to the development of GPS technology, the GPS has become a very useful instrument for collecting traffic data. GPS can reduce the cost of installation and maintenance in contrast with existing traffic detectors which must be stationed on the ground. But. there are Problems when GPS data is applied to the existing filtering techniques used for analyzing the data collected by other detectors. This paper proposes a method to provide users with correct traffic information through filtering abnormal data caused by the unusual driving in collected data based on GPS. We have developed an algorithm that can be applied to real-time GPS data and create more reliable traffic information, by building patterns of past data and filtering abnormal data through selection of filtering areas using Quartile values. in order to verify the proposed algorithm, we experimented with actual traffic data that include probe cars equipped with a built-in GPS receiver which ran through Gangnam Street in Seoul. As a result of these experiments, it is shown that link travel speed data obtained from this algorithm is more accurate than those obtained by existing systems.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.7
• /
• pp.297-306
• /
• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.3
• /
• pp.78-88
• /
• 2014

Now, UTIS collects and provides traffic information by building RSE 1,150(unit) and OBE about 51,000(vehicle). it's inevitable to enlarge traffic information sources which use to improve quality of UTIS traffic information for Stabilizing UTIS's service. but there are missing data sections. And, In this study as a way to overcome these problems, based on BIS(Bus information system) installed and operating in the capital area to develop normal vehicle's link transit time estimation model which is used realtime collecting BMS data, we'll utilize the model to provide missing data section's information. For these problem, we selected partial section of suwon-city, anyang-city followed by drive only way or not and conducted model estimating and verification each of BMS data and UTIS traffic information. Consequently, Case2,4,6,8 presented highly credibility between UTIS communication data and estimated value but In the Case 3,5 we determined to replace communication data of UTIS' missing data section too hard for large error. So we need to apply high credibility model formula adjusting road managing condition and the situation of object section.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.3 no.1 s.4
• /
• pp.97-107
• /
• 2004

As one of the most serious urban problems, routine city traffic congestion causes not only unpleasantness but also damage with increases of road tolls. Recently, many TDM plans are being improved along with plans to more effectively utilize established facilities and maximize the effect. To achieve the purpose of Intelligent Transport Systems(ITS). Recently, the core of ITS is Advanced Traveler information Systems (ATIS.) that are activity researched. A development of various muti-media system is very important of road guideline. First of all a business processing for offering travel information and give a consideration to the United states of various muti-media systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.5
• /
• pp.62-69
• /
• 2012

Traffic simulation models have been used for assessing various transportation strategies. Through comparing results from a simulation model and real field data, researchers try to show how close the model can reproduce the real world traffic. This model verification step is one of the most essential tasks in modeling procedure. Traffic counts and speeds have been frequently used for the verification or validation. Authors modeled severe PM peak bottleneck situation on the I-40 corridor in Raleigh, North Carolina using DYNASMART-P, a mesoscopic traffic simulation tool and verified the model. NCDOT has Traffic Information Management System which has archive capability for the traffic speeds on the I-40 corridor. However, the authors selected travel time as the field measure for model verification and collected the data using a GPS equipment because the speed data from NCDOT speed detectors are spot speeds which are not appropriate for comparison with link average speed from the simulation model. This paper describes the GPS field data collection procedure, the model verification method, and the results.

• The Journal of Information Technology
• /
• v.5 no.1
• /
• pp.143-156
• /
• 2002

Tourist Information Center has been played an important part of role in the promotion of tourism for both inbound and domestic market. The purpose of this paper is to examine the situation of our tourist information centers in context with information and personnel service. As a result we suggested some findings. According to studies, tourism information provided by TIC is critical and decisive for specific travel type and leisure travelers visit TIC more often than the other types of travelers. The specific aspects of tourism information is accuracy and currency which based on the characteristics of intangibility and perishability. According to this encouragement tourism information system should have to shifted to internet basis. This movement enabled tourism industry to make the atmosphere for portal or hub site for the effective operation of this system. The regionally networked system can make it possible to cope with some characteristics of tourism products. Reservations and information retrievals are major function of portal site. The data from suppliers (hotels, restaurants, event organizers, transportation, attractions etc) must be up-dated, controled by regional TIC and the connections should be extended among the regional TICs.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.3
• /
• pp.42-52
• /
• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.7
• /
• pp.3100-3116
• /
• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.

• Journal of information and communication convergence engineering
• /
• v.21 no.3
• /
• pp.225-232
• /
• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• Journal of Korean Society of Transportation
• /
• v.20 no.1
• /
• pp.7-18
• /
• 2002

To activate public transportation service, Bucheon City built Bus Information System based on Beacon type, and operates it for no.22 line. This research analyzes an effect of BIS operations, and mainly it analyzes far reliability evaluation of bus arrival time information and passenger satisfaction about BIS. As results of reliability evaluation of arrival time information service, it is proven to be practically inappropriate to use as arrival time data because it is not only travel time between each bus stop but also previous travel time history data. In order to improve this matter, neural network model was evaluated as the most outstanding one as result of experiment in applying current arrival time Prediction model. This research cannot help limiting for evaluation of operation effect in Bucheon City because there is no Bus Information System based on GPS type in Korea. For the future ITS model city, in the case of building ITS model city based on GPS type, it is possible to compare two systems relatively. In addition to that, fur the consideration of reliability of bus arrival time information, it is required to develop Predictable model and research factors that affect to bus operation.