• International Journal of Highway Engineering
• /
• v.17 no.3
• /
• pp.97-105
• /
• 2015

PURPOSES : The Toll Collection System (TCS) operated by the Korea Expressway Corporation provides accurate traffic counts between tollgates within the expressway network under the closed-type toll collection system. However, although origin-destination (OD) matrices for a travel demand model can be constructed using these traffic counts, these matrices cannot be directly applied because it is technically difficult to determine appropriate passenger car equivalent (PCE) values for the vehicle types used in TCS. Therefore, this study was initiated to systematically determine the appropriate PCE values of TCS vehicle types for the travel demand model. METHODS : To search for the appropriate PCE values of TCS vehicle types, a traffic demand model based on TCS-based OD matrices and the expressway network was developed. Using the traffic demand model and a genetic algorithm, the appropriate PCE values were optimized through an approach that minimizes errors between actual link counts and estimated link volumes. RESULTS : As a result of the optimization, the optimal PCE values of TCS vehicle types 1 and 5 were determined to be 1 and 3.7, respectively. Those of TCS vehicle types 2 through 4 are found in the manual for the preliminary feasibility study. CONCLUSIONS : Based on the given vehicle delay functions and network properties (i.e., speeds and capacities), the travel demand model with the optimized PCE values produced a MAPE value of 37.7%, RMSE value of 17124.14, and correlation coefficient of 0.9506. Conclusively, the optimized PCE values were revealed to produce estimates of expressway link volumes sufficiently close to actual link counts.

• Journal of the Ergonomics Society of Korea
• /
• v.28 no.3
• /
• pp.49-54
• /
• 2009

Visual occlusion method is a visual demand measuring technique which uses periodic vision/occlusion cycle to simulate driving environment. It became one of the most popular techniques for the evaluation of in-vehicle interfaces due to its robustness and cost-effectiveness. However, it has a limitation in that the vision/occlusion cycle forces the user to use the IVIS at a predetermined pace, while a driver decides when to use the device on his/her own in actual driving. This paper proposes a user-driven visual occlusion method for measuring the visual demand of in-vehicle interfaces. An experiment was conducted to examine the visual demand of an in-vehicle interface prototype using both the existing (system-driven) occlusion method and the proposed (user-driven) one. Two in-vehicle tasks were evaluated: address input and radio tuning. The results showed that, for the radio tuning task, there were significant differences in total shutter open time and resumability ratio between the methods. The user-driven visual occlusion method not only allows a better representation of drivers' behavior, but it also seems to provide more information on the chunkability of a task.

• Journal of Korean Society of Disaster and Security
• /
• v.14 no.2
• /
• pp.35-42
• /
• 2021

In order to produce electric vehicle demand forecasting information, which is an important element of the plan to expand charging facilities for electric vehicles, a model for predicting electric vehicle demand was proposed using Exponential Smoothing. In order to establish input data for the model, the monthly power demand of cities and counties was applied as independent variables, monthly electric vehicle charging stations, monthly electric vehicle charging stations, and monthly electric vehicle registration data. To verify the accuracy of the electric vehicle power demand prediction model, we compare the results of the statistical methods Exponential Smoothing (ETS) and ARIMA models with error rates of 12% and 21%, confirming that the ETS presented in this paper is 9% more accurate as electric vehicle power demand prediction models. It is expected that it will be used in terms of operation and management from planning to install charging stations for electric vehicles using this model in the future.

• International Journal of Highway Engineering
• /
• v.14 no.3
• /
• pp.163-171
• /
• 2012

Demand Responsive Transit (DRT) services are becoming necessary as part of not only alternative transportation means for elderly and mobility impaired passengers, but also sustainable and flexible transportation options in urban area due to the development of communication technologies and Location Based Services (LBS). It is difficult to investigate the system performance regarding vehicle operational schemes and vehicle routing algorithms due to the lack of commercial software to support door-to-door vehicle simulation for larger area. This study proposes a simulation framework to evaluate innovative and flexible transit systems focusing on various vehicle routing algorithms, which describes data-type requirements for simulating door-to-door service on demand. A simulation framework is applied to compare two vehicle dispatch algorithms, Nearest Vehicle Dispatch (NVD) and Insertion Heuristic (IH) for real-time shared-taxi service in Seoul. System productivity and efficiency of the shared-taxi service are investigated, comparing to the conventional taxi system.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.816-822
• /
• 2010

A comprehensive review for the selection of urban rail vehicle systems that best suit Gimpo railway line is taking place with consideration of the project area characteristics in light of line planning, passenger demand, supply of rolling stock, and railway construction and operation. Various aspects of vehicle systems including passenger demand on concerned lines, regional characteristics, vehicle types, and railway construction and operational settings should be taken into consideration. In addition, request for the introduction of customized vehicle systems reflecting the convenience of transit users such as wide and hospitable inner space, low noise, flexible operation of 2 to 4 car train-set and eye catching slim bridge piers is increasing. A study on alternatives to place an order to opt for optimum rolling stock systems considering line characteristics of Gimpo City's urban railway and future passenger demand while meeting the needs of Gimpo City has been conducted.

• International Journal of Highway Engineering
• /
• v.15 no.3
• /
• pp.177-189
• /
• 2013

PURPOSES: This study aims to suggest a proper left-turn treatment method for the bicycle traffic flow at four-legged intersections. METHODS: Four types of crossing methods are proposed and analyzed : (1) indirect left turn, (2) direct left turn, (3) direct left turn on a Bike Box, and (4) direct left turn on bike left turn lane. The VISSIM simulation tests were conducted based on forty-eight operation scenarios prepared by varying vehicle and bicycle traffic volumes. RESULTS : The results from the four-legged signalized intersections suggest that (1) the indirect left turn is appropriate when vehicle demand is high, (2) the direct left turn is efficient on most traffic situation but the safety is a concern, (3) the direct left turn on a Bike Box is appropriate when bicycle demand is high while vehicle demand is not, and (4) the direct left turn on a bike left turn lane is appropriate when both vehicle and bicycle demand are low. CONCLUSIONS : The direct left turn of bicycle provides more efficiency than the indirect left turn at the four-legged intersections but to apply the methods and to study more, advanced evaluation methods, related law, and insurance programs are needed.

• International Commerce and Information Review
• /
• v.16 no.3
• /
• pp.73-96
• /
• 2014

The purpose of this research is to evaluate a short-term export demand forecasting model reflecting individual passenger vehicle brands and market characteristics by using Vector Autoregressive (VAR) models that are based on multivariate time-series model. The short-term export demand forecasting model was created by discerning theoretical potential factors that affect the short-term export demand of individual passenger vehicle brands. Quarterly short-term export demand forecasting model for two Korean small vehicle brands (Accent and Avante) were created by using VAR model. Predictive value at t+1 quarter calculated with the forecasting models for each passenger vehicle brand and the actual amount of sales were compared and evaluated by altering subject period by one quarter. As a result, RMSE % of Accent and Avante was 4.3% and 20.0% respectively. They amount to 3.9 days for Accent and 18.4 days for Avante when calculated per daily sales amount. This shows that the short-term export demand forecasting model of this research is highly usable in terms of prediction and consistency.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1997.10a
• /
• pp.201-204
• /
• 1997

This study is focussed on optimization problems which require allocating the restricted inventory to demand points and assignment of vehicles to routes in order to deliver goods for demand sites with optimal decision. This study investigated an integrated model using three step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations. we developed several sub-models such as; first, an inventory-allocation model, second a vehicle-routing model based on clustering and a heuristic algorithms, and last a vehicle routing scheduling model, a TSP-solver, based on genetic algorithm. Also, for each sub-models we have developed computer programs and by a sample run it was known that the proposed model to be a very acceptable model for the inventory-allocation and vehicle routing problems.

• Journal of Advanced Marine Engineering and Technology
• /
• v.31 no.8
• /
• pp.911-917
• /
• 2007

Global primary energy demand is projected to increase by 1.7% per year from 2000 to 2030. Almost three-quaters of the increase in demand will come from the transportation sector. Fuel cell hybrid vehicle technology has the potential to significantly reduce energy and harmful emissions, as well as our dependence on foreign oil. In this paper, a systematic and logical methodology is developed and improved mainly to design light duty fuel cell hybrid electric vehicle. We investigated structure and characteristics of light duty FC hybrid vehicle carefully. It can easily be expanded to analyze vehicle-to-grid power connectable plug-in NeHEV. A fuel cell hybrid neighbourhood electric vehicle configuration has been studied in-depth utilizing the proposed methodology.

• Environmental and Resource Economics Review
• /
• v.32 no.3
• /
• pp.167-190
• /
• 2023

This study analyzes the potential demand for automobiles based on fuel type using survey data in Korea. The dependent variable of the model is the future desired fuel type, including gasoline, diesel, hybrid, electricity, and hydrogen. The main explanatory variables are the respondent demographic characteristics, key reasons for choosing vehicle fuel type and environmental awareness extracted via principal component analysis (PCA). Using a multinomial logit (MNL) model, we find that respondents who consider fuel economy and infrastructure increase the demand for a hybrid car but decrease the demand for electric and hydrogen vehicles. The denial-types increase the demand for gasoline (petrol) and diesel (light oil), and decrease the demand for electric vehicles. The anxiety-types increase the demand of hybrid vehicles, and decrease the demand for electric vehicles. In contrast, in the case of pro-types, the demand for diesel (light oil) hydrogen vehicles decreased.