• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.587-595
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• 2017

The study examinesthe hindrance factors including various laws and institutions with regard to the Unbundled Parking System (UPS) that has recently attracted the greatest attention as a way to manage traffic demand for sustainable development, efficient utilization of parking spaces, and to overcome the unstable housing market.The direction of improvement of related laws and institutions is also suggested. Its usage is proven by countries such as the United States of America and France, as they have already implemented this institution. To lay the foundation for the introduction of UPS of our own country, a survey on the preference for UPS was conducted. The survey equally divided 300 respondents into three clusters based on the sales price of apartments in Seoul. The analyses revealed that all three clusters have similar preferences (cluster 1: 68%, cluster 2: 62%, cluster 3: 65%) on UPS, and younger groups seem to answer in the affirmative more than the other age groups no matter what cluster they belong to. In conclusion, the results on the estimation of selection probability on the preference of unbundled parking system and sales discount rate are as follow. The groups of non-vehicle users have higher preference on UPS. When the discount rate is 14%, 69%, 77% and 62%ofrespondents would choose unbundled parking system for clusters 1, 2 and 3, respectively (￦6,370,000/PY,￦3,930,000/PY and ￦2,270,000/PY reduce when applying avg. sales price, respectively).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.581-589
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• 2021

With the recent increase in the introduction of micro-electric vehicles in Korea, interest in micro-electric vehicle user satisfaction is increasing to revitalize related markets. In this paper, a basic study was conducted on the development of public services using micro-electric vehicle based on the constituent factors of user satisfaction. The survey includes: ① 'Analytic Hierarchy Process (AHP) for selecting the priority factors of user satisfaction of micro-electric vehicles', ② 'A survey of micro-electric vehicles image' to collect data in advance for providing users' preferences and transportation services for micro-electric vehicles, ③ In order to investigate the user satisfaction level of users who actually operated micro-electric vehicles, the order of 'user satisfaction survey of micro-electric vehicle drivers' was conducted. In the Analytic Hierarchy Process (AHP) analysis, it was found that users regarded as important in the order of 'user utilization data', 'vehicle movement data', and 'charging service data'. In the micro-electric vehicle image survey, users perceived micro-electric vehicles more positively in terms of "safety", 'durability', 'Ride comfort', 'design', 'MOOE (Maintenance and other operating expense)', and 'environment-friendly' when comparing micro-electric vehicles with electric motorcycles. In the survey on the user satisfaction of micro-electric vehicle drivers, the use of micro-electric vehicle did not directly affect work performance efficiency, and there was an experience of being disadvantaged on the road due to the size of the micro-electric vehicle, and driving in a cluster of micro-electric vehicle for outdoor advertisements. The city's public relations effect was great, but it was concerned about safety. In the future, based on the results of this study, we plan to build a user satisfaction structural equation model, preemptively discover feedback R&D for micro-electric vehicle utilization services in the public field, and actively seek to discover new public mobility support services.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.233-248
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• 2012

The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1567-1572
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• 2012

An IPC(instrument panel Cluster) is a useful device that provides driving information to the driver. The information includes the vehicle speed, RPM, mileage, etc. The traditional IPC has been mostly implemented with mechanical technique. According to increment of needs for the convenience of IPC by user, the IPC must provide graphical interface and efficient driving information. Also the user-friendly IPC is needed by drivers. Thus flexible and robust software structure and development methods are required in order to develop IPC. In this paper, we propose software architecture and design method for the IPC using modeling method. We use MVC model and UML to model software architecture because they have flexible and robust characteristics. We can develop the various forms of information screen by separating views from model by using state diagram and class diagram in UML. Through this, the cost saving and ease of maintenance can be expected. The development time and cost can be reduced by using proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1321-1326
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• 2012

An IPC(instrument panel Cluster) is a useful device that provides driving information to the driver. The information includes the vehicle speed, RPM, mileage, etc. The traditional IPC has been mostly implemented with mechanical technique. According to increment of needs for the convenience of IPC by user, the IPC must provide graphical interface and efficient driving information. Also the user-friendly IPC is needed by drivers. Thus flexible and robust software structure and development methods are required in order to develop IPC. In this paper, we propose software architecture and design method for the IPC using modeling method. We use MVC model and UML to model software architecture because they have flexible and robust characteristics. We can develop the various forms of information screen by separating views from model by using state diagram and class diagram in UML. Through this, the cost saving and ease of maintenance can be expected. The development time and cost can be reduced by using proposed method.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.91-99
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• 2013

PURPOSES : This study aims at proposing the methodology for benefit evaluations in pavement maintenance methods and timings using KoPMS(Korean Pavement Management System) software which was developed for efficient pavement management. METHODS : This study classified pavement sections into 4 clusters considering AADT(Annual Average Daily Traffic) and ESAL(Equivalent Single-Axle Load) using cluster analysis and used the deterioration models in each cluster. Increased user costs due to pavement deterioration as time goes by and agent costs for maintenance were estimated. Based on deterioration model and KoPMS software, Methodology for benefit evaluation was proposed in pavement maintenance methods and with/without implementation using real pavement section data. RESULTS : This study verified that considering agent costs only would be constrained to decide pavement maintenance methods and timings, and ascertained that decision making with agent and user costs would be effective. In addition, this study revealed that pavement maintenance methods and timings can be affected by AADT and ESAL and frequent pavement maintenances can be more efficient for benefits in pavement sections with more AADT and ESAL. Also this study found that user costs would be more affected to decision making than agent costs. Moreover, Delay of conducting pavement maintenance caused increased vehicle operating costs and environmental costs because of poor conditions of pavements. CONCLUSIONS : This study proposed LCCA and benefit estimation methodology of pavement with considering agent and user costs. The results of this study can be used for baseline data of efficient pavement asset management.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.573-581
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• 2001

The purposes of this study are to estimate mean willingness to pay (WTP) for preventing forest fires by contingent valuation method (CVM), and to calibrate the variables affecting WTP. The forest fire prevention fund was utilized as a payment vehicle to elicit respondents' willingness to pay (WTP). A total of 500 adults who reside in Seoul Metropolitan area were selected by two-stage cluster sampling and conducted the face-to-face interview. The scenario was designed to meet the requirements for double-bounded dichotomous choice CVM. More than half of the respondents (64.6%) have a willing to pay for the fund. The mean WTP was \4,532. Therefore a total WTP for the population was \34,165,758,000. The calibration of Weibull proportional hazard model showed that education level, environmental conservation intention and negative consciousness about the effect of forest fire were independent variables strongly influencing the WTP.

• International Journal of Highway Engineering
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• v.7 no.3 s.25
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• pp.43-52
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• 2005

Highway classification is an essential part of defining design criteria of roads. This study is to classify highways by factor analysis. To accomplish the objectives, factor analysis is performed for classifying highways using the traffic data observed at the permanent traffic count points in 2004. A total off variables are applied : AADT, K factor, D factor, heavy vehicle proportion, day time traffic volume proportion, peak hour volume proportion, sunday factor, vacation factor and COV(Coefficient of Variation). The results of factor analysis show that variables are divided into two factors, which are the factor related to the fluctuational characteristics of traffic volume and the factor related to heavy vehicle and directional volume characteristics. According to the results of cluster analysis, 353 permanent traffic count points are categorized into such three groups as type I for urban highway, type II for rural highway, type III for recreational highway, respectively.

• Journal of KIISE
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• v.43 no.4
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• pp.404-410
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• 2016

Automated road map generation poses significant research challenges since GPS-based navigation systems prevail in most general vehicles. This paper proposes an automated detecting method for intersection points using GPS vehicle trajectory data without any background digital map information. The proposed method exploits the fact that the trajectories are generally split into several branches at an intersection point. One problem in previous work on this intersection detecting is that those approaches require stopping points and direction changes for every testing vehicle. However our approach does not require such complex auxiliary information for intersection detecting. Our method is based on partial trajectory matching among trajectories since a set of incoming trajectories split other trajectory cluster branches at the intersection point. We tested our method on a real GPS data set with 1266 vehicles in Gangnam District, Seoul. Our experiment showed that the proposed method works well at some bigger intersection points in Gangnam. Our system scored 75% sensitivity and 78% specificity according to the test data. We believe that more GPS trajectory data would make our system more reliable and applicable in a practice.