• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.413-418
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• 2020

The travel pattern of tourists for the development of the tourist course is designed to collect and analyze tourist information based on the big data of the carrier to improve the quality of the tourist course. In particular, the analyzed data is used to derive empirical data that can estimate the effect of tourists' inflow into tourism, and to utilize the information as basic data for the development of the tourist course. In addition, the travel pattern of tourists for the development of regional tourism courses is to collect and analyze information on the route and duration of tourists' travel based on big data collected by telecom operators, credit card companies and other data to improve the quality of tourist course development, and to derive empirical data to estimate the effect of tourist inflow through the analyzed data, based on the characteristics of the tourism course and the data needed for the development of new tourist courses in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.409-416
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• 2006

Real-time traveler information disseminated through Variable Message Signs (VMS) is known to have effects on driver route choice decisions. In the past, many studies have attempted to optimize the system performance using VMS message content as the primary control variable of driver route choice. This research proposes a VMS information provision optimization model which searches the best combination of VMS message contents and display sequence to minimize the total travel time on a highway network considered. The driver route choice models under VMS information provision are developed using a stated preference (SP) survey data in order to realistically capture driver response behavior. The genetic algorithm (GA) is used to find the optimal VMS information provision strategies which consists of the VMS message contents and the sequence of message display. In the process of the GA module, the system performance is measured using micro traffic simulation. The experiment results highlight the capability of the proposed model to search the optimal solution in an efficient way. The results show that the traveler information conveyed via VMS can reduce the total travel time on a highway network. They also suggest that as the frequency of VMS message update gets shorter, a smaller number of VMS message contents performs better to reduce the total travel time, all other things being equal.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.95-110
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• 1995

n this research neural -based model was developed to forecast link travel times , And it is also compared wiht other time series forecasting models such as Box-Jenkins model, Kalman filter model. These models are validated to evaluate the accuracy of models with real time series data gathered by the license plate method. Neural network's convergency and generalization were investigated by modifying learning rate, momentum term and the number of hidden layer units. Through this experiment, the optimum configuration of the nerual network architecture was determined. Optimumlearining rate, momentum term and the number of hidden layer units hsow 0.3, 0.5, 13 respectively. It may be applied to DRGS(dynamic route guidance system) with a minor modification. The methods are suggested at the condlusion of this paper, And there is no doubt that this neural -based model can be applied to many other itme series forecating problem such as populationforecasting vehicel volume forecasting et .

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.3
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• pp.129-138
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• 2018

The purpose of this study is to analyze the daily living area of the elderly using the vast amount of travel route data collected through smart phones. In order to analyze the utilization status of the elderly into the visiting area and the living area, the subway station influence area was typed based on the number and ratio of the elderly visiting and the elderly living there. The characteristics of the elderly visiting area and the living area of the subway station area were derived by analyzing the walking route data for the three types of subway station influence areas where the elderly visit and live. First, we derive the range of visiting area and living area of the elderly near the subway station. Second, we derive the characteristic of moving distance which causes the linked walking of the elderly. Third, destination distribution and facility utilization are influenced by the subject of use, movement pattern, and facility awareness.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.31-43
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• 2008

Travel time prediction is an indispensable to many advanced traveler information systems(ATIS) and intelligent transportation systems(ITS). In this paper we propose a method to predict travel time using $Na{\ddot{i}}ve$ Bayesian classification method which has exhibited high accuracy and processing speed when applied to classily large amounts of data. Our proposed prediction algorithm is also scalable to road networks with arbitrary travel routes. For a given route, we consider time-varying average segment velocity to perform more accuracy of travel time prediction. We compare the proposed method with the existing prediction algorithms like link-based prediction algorithm [1] and Micro T* algorithm [2]. It is shown from the performance comparison that the proposed predictor can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.4
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• pp.229-235
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• 2014

This paper presents an environmental navigation system which provides a guidance to the users of smart bicycle for a pollution-free route during their travel. The smart bicycle operates as a sensor node being composed of a distributed wireless sensor network over the whole urban area. Several environmental sensors measuring the amount of dust, CO, $CO_2$, $NO_2$ in the air are built into the smart bicycle to estimate the level of air pollution in the located area. Each smart bicycle sends/receives the measured sensor data and the city pollution map to/from the centralized server, which leads the bike-riders to a healthy route by providing the environmental navigation information. The proposed idea and its implementation give a useful insight on various application services with the distributed smart bicycles.

• Journal of Urban Science
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• v.10 no.1
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• pp.49-60
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• 2021

The purpose of this study is to analysis the impact on the inside of the new city when an incidents occurs on the Songdo International City connecting road, which has a limited access. The analysis data used KTDB's O/D and network data of the Seoul metropolitan area. In addition, the scenario composition applied a method of reducing the number of lanes on the road according to the situation of incidents, targeting bridges advancing from Songdo International City to the outside in the morning peak hours. The analysis method analyzed the traffic volume, total travel time, total travel kilometer, and route change in the new city based on the results of the traffic allocation model. As a result of the analysis, the range of influence was shown to two types. First, of the seven bridges, Aam 3, Aam 2, and Aam 1 were analyzed to have an impact only in some areas of the northwestern part of the new city. On the other hand, the remaining bridges were analyzed to affect the new city as a whole. The analysis results of this study are expected to be used as basic data to establish the scope of internal road network management when similar cases occur in the future.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.135-156
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• 2012

The purpose of this study is to ascertain librarian's perceptions on their users' library access and its patterns. Interviews with seven library staff reveal physical accessibility issues including spatial relationships between libraries and other facilities such as shopping malls and schools, travel distance, transportation mode, and temporal perspectives of library access. The results from the interviews corroborate the findings from secondary analysis using household travel data. However, interviewees do not have a clear picture of how much their users travel and spend to access their libraries. This is true, even though these factors are critical to analyze physical accessibility. Based on the findings, this study makes recommendations to improve the accessibility of public libraries. Suggestions include the concept of sponsorships with other facilities, the placing of material drop-boxes on the main route, and providing library programs during lunch time.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.47-60
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• 1999

In this study, the dynamic route choice behavior of driver is assumed to be affected by the current conditions of traffic environments as well as the Past traffic environments and activities. The repeated survey of multi-timed to owner drove in Chon-ju city by the virtual traffic information system was performed by the stated preference method. And the LISREL(An analysis of linear structural relationship) model was used. As the results. the variable Parameter and t-value of travel time information on applied model was high and their results have an effect greatly to the route choice. After all, the route choice was negative from Kirin-ro, which Penetrates the downtown, and positive from Chunbyun-ro which was a roundabout way was confirmed. Estimated result of the reasonability, the highest suitable model was ode which applied the concept of serial correlation and stated dependence and was shown applying rightfulness to dynamic model. As the serial correlation and stated dependence parameter value, when time interval was large, parameter value was small and the serial correlation and stated dependence was in inverse proportion ratio to the time interval.