• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2465-2471
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• 2013

This paper develops a travel time prediction algorithm that can be used for real-time application. The algorithm searches for the most similar pattern in historical travel time database as soon as a series of real-time data become available. Artificial neural network approach is then taken to forecast travel time in the near future. To examine the performance of this algorithm, travel time data from Gyungbu Highway were obtained and the algorithm is applied. The evaluation shows that the algorithm could predict travel time within 4% error range if comparable patterns are available in the historical travel time database. This paper documents the detailed algorithm and validation procedure, thereby furnishing a key to generating future travel time information.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.161-170
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• 2007

The purpose of this study is to find the solution that overcomes the existing assumption of symmetric cost functions in multi-class assignment. In the assignment problem, the assumption of a symmetric cost function means that the link cost is determined by each unique mode and is not affected by any other modes. In this study, the authors have applied a diagonalized algorithm and a heuristic model based on column generation to a multi-class assignment model and analyzed the result. Through the study, the authors found that the diagonalized algorithm produces equilibrium solutions by the initial convergence condition. In contrast to the diagonalized algorithm, the column generation algorithm has improved the solution model to overcome the problem of equilibrium solutions in the diagonalized algorithm.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.19-32
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• 1999

In this study, the trip characteristics of workers in the city are systematically analyzed. The trip behaviors and socioeconomic characteristics of workers are analyzed using Person Trip Survey Data of 1988 and 1992 in Taegu Metropolitan area. With the results of behavioral analyses, the daily travel pattern of workers is shown as one tour contained two trips and it is relatively simple and stable. Also the rate using the same mode in a day is Presented as high ratio. So, it can be explained that the choice of worker\`s first trip is fixed his/her travel mode for his/her daily travel mode. Based on these analyses, the mode choice model for workers is developed by applying the Multi-nominal Logit Model with the choice set of bus, taxi, and car. The explanatory variables of this model include sex, age, auto, travel time, and cost. Empirical tests of the model show encouraging results. After that, the temporal transferability of the model is examined by the Pairwise t-test and five indexes far the model of 1988 and 1992. The results of examination are satisfied with each significance level of the explanatory variables and five indexes. Therefore. it can be concluded that the temporal transferability of this model developed in this study is resonable.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.89-100
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• 2008

In an urban network controlled by traffic signals, there is an interaction between the signal timing and the routes chosen by individual road users. This study develops a bi level programming model for traffic signal optimization in networks with path based traffic assignment. In the bi level programming model, genetic algorithm approach has been proposed to solve upper level problem for a signalized road network. Path based traffic assignment using column generation technique which is proposed by M.H. Xu, is applied at the lower-level. Genetic Algorithm provieds a feasible set of signal timings within specified lower and upper bounds signal timing variables and feeds into lower level problem. The performance of this model is investigated in numerical experiment in a sample network. In result, optimal signal settings and user equilibrium flows are made.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.23-35
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• 2009

This study proposes a methodology for estimating representative section travel times using individual vehicle travel information under the ubiquitous transportation environment (UTE). A novel approach is to substantialize a concept of dynamic node-links in processing trajectory data. Also, grouping vehicles was conducted to obtain more reliable travel times representing characteristics of individual vehicle travels. Since the UTE allows us to obtain higher accuracy of vehicle positions, travel times for each lane can be estimated based on the proposed methodology. Evaluation results show that less than 10% of mean absolute percentage error was achievable with 20% of probe vehicle rate. It is expected that outcome of this study is useful for providing more accurate and reliable traffic information services.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.119-128
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• 2010

Mode choice behavior is associated with travelers' latent behavior that is an unobservable preference to travel behavior or mode characteristics. This paper specifically addresses the problem of unobservable factors, that is latent behavior, in mode choice models. Consideration of latent behavior in mode choice models reduces the errors that come from unobservable factors. In this study, the authors defined the latent variables that mean a quantitative latent behavior factors, and developed the combined RP/SP model with latent variables using the mode choice behavior survey data. The data has traveler's revealed preference of existent modes along the Han River and stated preference of new water transit on the Han River. Also, The data has travelers' latent behavior. Latent variables were defined by factor analysis using the latent behaviour data. In conclusion, it is significant that the relationship between traveler's latent behavior and mode choice behavior. In addition, the goodness-of-fit of the mode choice models with latent variables are better than the model without latent variables.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.288-298
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• 2017

The system of high-speed and conventional railway vehicles is diversified, and significant technological development in performance has been achieved. This study analyzed the modal change characteristics; furthermore, it estimated the value of travel time by improving the travel time and cost for the passenger's perception of railway. In this study, we formulate a mode choice model for passengers and compare it with the mixed logit model which reflects individual taste variation. In addition, the validity of the analysis is presented through an estimation the value of travel time using the derived model. For this purpose, a stated preference survey was conducted with 510 people using public transportation. The benefits of time-saving can be accurately determined by estimating the value of time spent on the railway. Appropriate fares for public transportation can also be estimated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.1-11
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• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.7-16
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• 2004

In mode choice decision, travelers consider not only travel time but also reliability of its modes. In this paper, reliability was expressed in terms of standard deviation and maximum delay that were measured based on triangular distribution. In order to estimate value of time and value of reliability, the Multinomial and Nested Logit models were used. The analysis results revealed that reliability is an important factor affecting mode choice decisions. Elasticity is used to estimate the impacts of the different policies and system improvements for water transportation mode. Among these policies, decision maker can assess and select the best alternative by doing the benefit and cost analysis based on a new market share, the value of time, and the value of reliability. Finally, a set of promising policies and system improvement of the water transportation were proposed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.22-39
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• 2021

This study estimated mode choice models for access travel and neighborhood travel from an SP survey in metropolitan areas where shared e-scooter services are offered. Model results show that travel time and travel cost have negative effects on mode utility. It is also revealed that people are more sensitive to travel time in access travel, whereas they are more influenced by travel cost in neighborhood travel. Looking at individual and household attributes, it has a positive effect when under 40 yerars of age, owning bikes, being a public transportation user, while it has been shown a negative effect in less than 3 million won in monthly household income and owning individual cars.