• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.135-145
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• 2016

This study assumes a vehicle choice model based on the multinomial model and analyzes the vehicle choice behaviors of consumer. An SP survey targeting drivers was implemented and data was collected for model estimates, with the possible choice options of the survey takers limited to gasoline, HEV, PHEV, and EV vehicles. The explanatory variable mostly displayed a significance level of under 5%, and excluding variables for price and fuel the remaining variables were all consistent with the logical direction with the plus (+) sign and the results were determined to be rational. Consumers selecting mid-size & full-size vehicles are able to afford more than consumers that selected other vehicle types, so there was relatively little consideration given to low fuel costs when compared to vehicle price. For this reason, it was determined that for the full-size vehicle model the fuel variable could be disregarded. Socio-economic variables that were statistically significant were the age and infor variables for the sub-compact & compact, the age, infor and inc3 variables for the mid-sized & full-size vehicles.

• Proceedings of the Technology Innovation Conference
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• 2006.02a
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• pp.264-297
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• 2006

In this paper, we attempt to analyze consumer preference for the alternative-fuel vehicles based on data from a stated preference using the conjoint analysis. Five possible fuel types (gasoline, diesel, CNG, LPG, Hybrid (electricity+gasoline)) are covered in conjoint cards. To estimate and analyze consumer preference, discrete choice model is used. Specifically, Bayesian mixed logit model is used. Based on estimating results, we discuss the business strategy and policy for the alternative fuel vehicle.

• Journal of Korean Society of Transportation
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• v.7 no.1
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• pp.19-34
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• 1989

In general, Shopping centers are located in the center of transportation, which induce more traffic concentration than other facilities. As a result, it becomes to one of the aggravating factors of urban ＆ transportation problem such as traffic conjestion, parking problems. Thus, in planning shopping-center, it is desirable that consumer\`s trip pattern is should lie more carefully analyzed in order to alleviate the above problems. This study is aimed at finding the characteristics of shopping tripes and analyzing the choice behavior of shopping center and mode-to-shop. This study has developed a nested logit model in which consumers choose shopping center and mode-to-shop with a sequential structure. The model was estimated using household data from the 1989 May, Seoul metropolitan area and the 18 alternatives of shopping center and 5 mode alternatives. The estimated model have been evaluated and it may be concluded that this model for shopping trips is effective and fesible. The conclusion of this study are as fellows. 1. Out-of-vehicle travel time is more important factor affecting behavior of mode choice than in-vehicle travel time. 2. All of direct-elasticities for mode with respect to the travel time is more elastic than travel cost. 3. Accessibility to shop is more important factor affecting the choice of shopping center than parking space. 4. The value of out-of-vehicle travel time exceeds the value of in-vesicle travel time by 1.64 times.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.113-123
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• 2011

Recently, the global warming problem has arised around world, many nations has set up a various regulations for decreasing $CO_2$. In particular, $CO_2$ emissions reduction effect is very powerful in transport part, so there is a rising interest about development of green car, or electric vehicle in auto industry. For this reason, it is important to make a strategy for charging infra and forcast electric power demand, but it hasn't introduced about demand forecasting electric vehicle. Thus, this paper presents a demand forecasting for electric vehicles using choice based multigeneration diffusion model. In this paper, it estimates innovation coefficient, immitation coefficient in Bass model by using hybrid car market data and forecast electric vehicle market by year using potential demand market through SP(Stated Preference) experiment. Also, It facilitates more accurate demand forecasting electric vehicle market refelcting multigeneration diffusion model in accordance with attribute progress in development of electric vehicle. Through demand forecasting methodology in this paper, it can be utilized power supply and building a charging infra in the future.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.133-141
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• 2007

The study examines households' auto ownership and car type choice with a nested legit model. In summary. ${\rho}^2$ and the inclusive values, which represent the goodness of fit of the model, are statistically significant. Therefore. the nested logit model is superior to the standard legit model in this case. Also. the elasticity of operating costs is larger than 1, which means households' car ownership and car type choice is very sensitive to the operating costs. Finally, the elasticity of the operating costs in the lower income group is higher than that or the operating costs in the higher income group.

• Ocean and Polar Research
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• v.36 no.3
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• pp.277-288
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• 2014

The Korean government is considering the implementation of a project to develop a deep-sea human-operated vehicle (HOV) to improve the level of deep-sea research. Information on the scientific benefits from the project is urgently needed in order to come to a decision about whether to implement the project. This paper measures the conservation value of developing nine attributes associated with HOV by using the choice experiment (CE). A survey of about 356 experts was undertaken and 132 experts completely responded to the survey. To deal with the CE data from the survey, we employed a multinomial logit model. All the coefficient estimates are statistically significant and consistent with prior expectations. Therefore, we can judge that the respondents' works required in the CE survey were within their cognitive abilities and they reported responsible and significant values. Each marginal willingness to pay for each attribute associated with the HOV is statistically significant and provides good information on the scientific values with regard to developing the HOV. The results can be utilized in evaluating and planning several alternatives related to developing the HOV.

• 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.

• 한국ITS학회:학술대회논문집
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• 2010.05a
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• pp.196-203
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• 2010

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.54-63
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• 2017

With the aim of promoting the use of metropolitan railways, the present research developed a mode choice model for evaluating its competitiveness against passenger cars. A case study was carried out with Gyeongeui and Joongang line, and the area of interest was the direct operating railway between Ilsan and Guri station where the two lines intersect. The mode choice model was a disaggregate behavior model which used Stated Preference (SP) survey data, and the plot of competition was between private passenger cars and express trains. As a result, the mode choice model was established, and this model was used to analyze characteristics of passengers' time value and elasticity. It was shown that reducing travel time is more efficient than reducing travel cost when it comes to operating express trains in metropolitan railways. Therefore, policies designed for activating the use of metropolitan railways should expand direct operating service of individual lines and run more express trains in order to minimize transfer and in-vehicle time.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.2
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• pp.74-81
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• 2012

The purpose of this study provides the theoretical model for protecting the economic and social loss from the current alternative fuel vehicle which is developed without compatibility and senseless one's own through verifying the statistical significant by method of measuring analysis. The market scale of alternative fuel vehicle depends on customer's and station's expectation about the number of potential vehicle users. It is very difficult for vehicle manufacturer to make a decision on the standard alternative fuel vehicle as it might reduce profit and market share. Accordingly, the development of alternative fuel vehicle should have manufacturer confident on the potential profit in the future. Moreover, if we decide to use the non-standard fuel after we started to use the standard fuel, it would take a huge cost comparing with starting to use the standard fuel only. As a result, once one of companies starts to provide the non-standard fuel service, it is getting more difficult to use the standard fuel going forward. Consequently, we may review the possibility of choice on the standard fuel before the vehicle manufacturer starts service with non-standard fuel.