• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2005.11a
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• pp.311-314
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• 2005

Our city structure is being complicated from the development of industry and the increase in population. It makes the ground space overcrowded, so underground space is systematized for use. Because this underground space has very complicated configuration, people have difficulty in finding the route in the underground space. Therefore It is demanded to comprehend configuration of the various space structure, predict pattern of the moving and analyze induction factor of the moving. When people are in the conflagration or dangerous situation, they are in the habit of using the route which they are used to go to and from. It is needed to analyze moving pattern of the pedestrian who usually use the underground space for the sake of dealing with conflagration in the underground space. Finally, this study suggested that general characteristic, distribution, moving route of the pedestrian and factors influencing that they choose the route which the research finds out.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.77-87
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• 2010

In the last five years, Korea has supplied many more bicycle facilities than in the last several decades combined. However, have bicyclists increased in proportion to investment? If bicyclists are avoiding existing bicycle related facilities, including off-road bicycle facilities, it could be because suppliers did not consider bicyclists' preferences in their planning process. In this paper, the authors tried to understand the bicyclists' behavioral and route choice characteristics using stated preference surveys and a logit model, using commuting time in Daejeon Metropolitan City, Korea. The results show that nine factors affect the route choice behavior of bicyclists. In particular, bicyclists preferred sub-arterial roads to off-road, dedicated bicycle facilities in residential area. It means that bicyclists like a seamless bicycle route and that a buffer zone between car lanes and bicycle lanes or 50 km/h speed limits for cars are necessary for bicycle lanes that are not physical separated.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.5-29
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• 1995

Advanced Traveler Inoformation Systems*ATIS) , as a subsystem of ITS influence the travel choices of dreivers by providing them with historical, real-time and predictive information to supprot travel decisions and consequently improves the speed and quality of travel. For thesuccessul accomplishment of ATIS, the time-dependent variations of traffic in a road network and travel times of vehicles during their journey must be predicted . The purpose of this study is to evaluate the past developments in the dynamic route choice models and to apply the instantaneous dynamic user optimal route choice model. recently formulated with flow propagation constraints by Ran, Boyce and LeBlanc, to the real transportation network of Seocho-Ku in Seoul. As input data for this application, the time-dependent travel rates are estimated and the link travel time function is derived. The modelis validated from three view points : the efficiency of model itself the ability to predict traffic volume and travel time on links, and the optimal traffic control.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.14-25
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• 2020

This research proposes a methodology to evaluate the rationality of passengers' route choice who make trips within Seoul metropolitan subway based on smart card data. The rationality of user route choice is divided into the degree of determinacy and similarity concepts as basic principle. Determinacy is the degree to which the route selected by the passenger is identical to the system optimal path. Similarity indicates the degree to which the route is similar to the system optimal path. The K-path search method is used for path enumeration, which allows for measurement of determinacy. To assess determinacy within similarity, transfer tag data of private operators is used. Consequently, the concept of similarity applied to the model is such that the passenger's path choice is identical to the path taken using the tag reader. Results show that the determinacy of appearance of the shortest path (K=1) is 90.4%, while the similarity of appearance as K=(2-10) is 7.9%, summing to 98.3%. This indicates that trips on the metropolitan subway network are being rationally explained. 1.7% of irrational trips are attributed to the unexplainable error term that occurs due to the diversity of passengers.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.599-604
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• 2010

In this study, the value of travel time was estimated with reflecting the fuel cost according to travel distance. The main objective of this study is whether the addition of the fuel cost as a factor for route choice behavior is appropriate or not, through the stated preference survey. The route choice model was developed using SP survey technique with the consideration of level difference and the value of travel time, toll and fuel costs. Consequently, the fuel cost is identified as a main factor like travel time and toll cost in choosing routes from drivers' viewpoints. Nevertheless, since toll costs are recognized as out-of-pocket expenses whereas fuel costs as periodical expenses, it seems drivers are more sensitive to toll than fuel costs.

• Journal of Korean Society of Transportation
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• v.5 no.1
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• pp.3-23
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• 1987

Traffic signal control problems in urban street networks are formulated in two ways. In the formulations network flows are assumed to satisfy the user route choice criterion. the first formulation which is called implicit substiuation incorporates user route behavior implicitly in the objective function by recognizing the dependence of the link flows on the signal variables. On the other hands, the second one which is called 'penalty formulation' consists in expressing the route choice conditions in the form of a single nonlinear constraint. Approximate solution algorithm for each of the formulations was investigated in detail and computer codes were written to examine key aspects of each algorithm. A test was done on a network which is small in size but sufficiently complex in representing real-world traffic conditions and the test result shows that both algorithms produce converged solutions. It is recommended, however, that further studies should be done in order to compare the performance of each algorithm more in depth.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.92-100
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• 1995

Fuzzy reasoning has been applied to analysis of traffic problems on urban arterial road. As the analysis on factors of route choice has been already carried out, its result can be used for construction of the model. Route choice rate estimation by fuzzy reasoning was discussed from its structure and accuracy. The major objective of the study is to introduce some kinds of methods with fuzzy reasoning and to make their feature obvious. First, the production system model is introduced with consideration of reality to actual travel behavior. Second, overlapping areas of fuzzy language function are investigated. Finally, process of fuzzy reasoning was also considered. Five kinds of Fuzzy reasoning are compared to investigate in relation between shapes of membership function and estimation validity.