• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.767-777
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• 2010

This paper investigates the relationship between the passenger car demand and business activities in the OECD. The positively linear relationships changed suddenly since 1990 and the reason was thought to be the polarized economic development of USA and Japan. The cases of other countries supports this conclusion. According to the conclusion, we modeled and estimated the car demand function of Korea.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.1-8
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• 2014

Safety performance of a new car is evaluated through USNCAP and their results in the star rating are provided to the consumers. It is very important to obtain high score of USNCAP to appeal their performance to consumers. Therefore the car companies have made the effort to improve their car safety performance. These efforts should satisfy the demand not only to get high score but also to pass the FMVSS, NHTSA regulations on safety. Huge numbers of car crash tests have been conducted on these bases by car companies. However physical tests spend too much cost and time, as an alternative way, the simulation on the car crash could be a solution to reduce the cost and time. Therefore the simulations have been widely conducted in car industry and various researches on this have been reported. In this study, restraint system had been optimized to minimize the injury of female passenger. Belted $5^{th}%ile$ female frontal crash test was selected from various test methods of USNCAP for the study. Initial velocity of the test was 56km/h. The combination injury probability of USNCAP was selected as an objective function and the injury limit value, which was defined in FMVSS, was set to an optimization constraint. Many researches that were similar to this study had been conducted, however most of them had limitation that interaction between airbag and safety belt had not been considered. Contrary to these researches, the interaction was considered in this study.

• Journal of the Korean Institute of Landscape Architecture
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• v.19 no.2
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• pp.12-22
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• 1991

The purpose of this study is to identify demand and methods of projection, including to prove the variables affecting the fluctuation of visitors and to analyze the relationship between these variables in National Park. Statistical analysis method (Multiple Linear Regression Analysis, ANOVA, and Model diagnostics) was carried out by computer program SAS/pc. 13 variables (1. Total Population, 2. Per Capita PDI, 3. Employment Ratio of S.O.C. & others, 4. NO. of Passenger Car, 5. Length of Roads, 6. Leisure Expenditure of Farm Household, 7. Leisure Expenditure of Urban Household, 8. Price Index, 9. NO. of Bus, 10. Exchange on Dollars, 11. Export, 12. Import, and 13. Visitors in National Park) had been used to this study. The scope of time period is during the last 17 years (1970-1986). The results were as follows; 1) Participation depends only on the specific characteristics of the economic factors (Price Index and Leisure Expenditure of Urban Household). These factors are the importance factors directly affecting the participation of visitors. The statistical Model for projecting the visitors in National Parks is the function of "Visitors in National Parks (thousand)=14915+0.210311*Leisure Expenditure of Urband Household (won)-157.835619*Price Index(1985=100)" 2) The external factors affecting the participation depends upon the interelated features of availability and accessibility (NO. of Passenger Car, Length of Roads, and NO. of Bus) of recreation resources or sites, and the economic factors (Per Capita PDI, Export, and Import). These factors are the factors indirectly affecting the participation of visitors. 3) The participation depends on the specific characteristics of demographic factors (Total Population and Employment Ratio of S.O.C. & others). These factors are the factors indirectly affecting the participation of visitors. 4) The unexpected fluctuation of yearly visitors depends on oil shock or inflation (1971, 1973-1974, 1979-1980), promulgation of national emergency decrees (1971-1972, 1974-1975, 1979-1980), and national events (assassination of president Park's wife, Madame Yuk in 1974 and president Park I 1979).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.118-133
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• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.77-88
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• 2001

Until now, though most of the studies related to demand estimation method using traffic counts use methods based on singleclass, travel demands or flows are made by mixing various vehicles in real networks. In general, existing demand estimation methods based on traffic counts estimate O/D by converting a multiclass O/D matrix and traffic counts into a singleclass O/D matrix and traffic counts through PCE conversion, and analyze a O/D matrix by dividing into a multiclass O/D matrix and traffic counts after multiplying an estimated O/D matrix by the fixed ratio of a singleclass O/D matrix and traffic counts before PCE conversion. However, the merits of a demand estimation method based on multiclass calculate each route choice ratio about multiclass O/D, and maximize the estimation capability of multiclass by calculating each gradient, the reduction direction of objective function. Therefore, this study aims to establish a demand estimation method which considers congestion between vehicle and vehicle by using multiclass instead of singleclass.