• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.51-61
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• 2023

Travel demand estimation of E-Scooter is the start point of solving the regional demand-supply imbalance problem and plays pivotal role in a linked transportation system such as Mobility-as-a-Service (a.k.a. MaaS). Most focuses on developing trip generation model of shared E-Scooter but it is no study on selection of an appropriate zone scale when it comes to estimating travel demand of E-Scooter. This paper aimed for selecting an optimal TAZ scale for developing trip distribution model for shared E-Scooter. The TAZ scale candidates were selected in 250m, 500m, 750m, 1,000m square grid. The shared E-Scooter usage historical data were utilized for calculating trip distance and time, and then applying to developing gravity model. Mean Squared Error (MSE) is applied for the verification step to select the best suitable gravity model by TAZ scale. As a result, 250m of TAZ scale is the best for describing practical trip distribution of shared E-Scooter among the candidates.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.1-12
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• 2024

Pedestrian facilities encompass pedestrian roads, stairs, and queuing areas exclusively designed for pedestrian use. The Korean Highway Capacity Manual provides guidelines for analyzing the capacity and level of service of pedestrian facilities. However, there is a lack of analysis methods tailored specifically for pedestrian facilities. Therefore, in this study, we introduced a new standard of pedestrian space to account for changes in the Korean body ellipse. Furthermore, based on this newly defined pedestrian space, we proposed a new standard value for the level of service of queuing areas. The results of on-site surveys confirmed that the proposed level of service can effectively reflect the actual walking situation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.26-41
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• 2024

To ensure safer road conditions, understanding the human factors influencing driving behavior is crucial. However, there are many difficulties in deriving the characteristics of individual human factors that affect actual driving behaviors. Therefore, this study analyzes self-reported dangerous-driving propensities in order to explore potential correlations with drivers' behaviors. The goal is to propose a method for assessing driving tendencies based on varying traffic scenarios. The study employed a questionnaire to gauge participants' propensity to drive dangerously, utilizing a simulator to analyze their driving behaviors. The aim is to determine any notable connections between dangerous-driving propensity and specific driving behaviors. Results indicate that individuals exhibiting a high propensity for reckless driving, as identified by the Korean DBQ, tend to drive at higher speeds and display more aggressive acceleration patterns. These findings contribute to a potential method for assessing reckless driving drivers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.89-105
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• 2024

Bus stop improvement conveys users their usability. It is essential that transportation jurisdictions should identify quantitative effects of a bus stop improvement to invest effectively and expand consistently. Nevertheless, there is currently no research to estimate the quantitative effect on bus stops improvement. In this study, the willingness to pay and the benefit-cost ratio for the bus stops improvement were estimated through a contingent valuation method based on user satisfaction. It was found that the bus stop improvement located in urban areas can achieve high-cost benefits, and it in suburban areas has a great impact on improving the quality of life of local residents. The results of this study will be used as a basis for expanding the bus stop facility improvement project.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.284-298
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• 2023

With the rapid advances in automated driving technology, opportunities to experience automated driving directly or indirectly are being provided to the public. On the other hand, research on the preferred automated driving patterns from the user's perspective has not been conducted in Korea. This study used a driving simulator and an experimental vehicle capable of automated driving to evaluate the user satisfaction regarding longitudinal and lateral accelerations. Automated driving patterns were implemented in a virtual environment simulation using five values of longitudinal and lateral accelerations derived from driving experiments. Among these values, three were implemented through experimental vehicle-based automated driving to evaluate satisfaction and anxiety. The participants evaluated lateral acceleration more sensitively than longitudinal acceleration and showed higher levels of anxiety. Based on these results, the necessity of user-oriented evaluation research for automated driving patterns and the suitability of simulator-based evaluation methods were presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.77-91
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• 2023

Recently, there has been a worldwide increase in research and development on automated vehicles for commercialization. It is expected that the use of level 3 autonomous vehicles on continuous-flow roads will be introduced and will increase. Consequently, various studies have been conducted to investigate the impact of mixed traffic flow with automated vehicles based on the market penetration rate (MPR). However, these studies have been conducted independently, and the results have shown different trends. Therefore, this study attempted a quantitative analysis of the impact of automated vehicles on mixed traffic flow on uninterrupted roads through a meta-analysis. The results showed that the effect size estimated from an MPR of 75% or higher was statistically significant.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.17-28
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• 2024

In this study, the capacity of the tunnel and the general section was calculated and compared using the VDS detector data, and the decrease rate in capacity of the tunnel section was analyzed by tunnel type. To compare the capacity of the tunnel and the general section, the Product Limit Method (PLM) was applied to the VDS detector data. As a result of comparing the capacity of the tunnel and general section, the capacity of the tunnel section decreased by about 6.5% compared to the general section. To classify the tunnel type, the tunnel extension and the number of lanes were used as variables, and there was a difference in the decrease rate of capacity by tunnel group classified by each criterion.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.29-47
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• 2024

Many domestic and foreign studies derive factors that significantly affect the use of shared E-scooters based on performance data, but few studies have been conducted with comparative analysis models using predictive power, applying them to other regions. Therefore, by clearly establishing detailed influencing factors and scope in Gwangjin-gu and Gangnam-gu by using domestic shared E-scooter performance data, this study enhances predictive power, and the Geographically Weighted Regression model is derived through spatial autocorrelation verification. Based on the results, the direction of a construction model created from regional differences was presented, and major implications from the user's perspective are derived based on the difference between actual use and the model's prediction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.1-15
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• 2024

The COVID-19 pandemic significantly impacted societies, particularly the elderly with higher susceptibility and mobility constraints. This study investigates COVID-19's influence on elderly travel at subway stations using card data. Analyzing pre/post-COVID-19 data via multilinear regression, we found factors like subway transfer lines, presence of rivers, the area of traditional markets, number of traditional Korean medicine clinics, number of cultural facilities, and number of large commercial facilities correlated positively with elderly travel. Post-COVID-19, effects of variables related to public transportation and employment, and indoor leisure facilities decreased, while the effects of outdoor and traditional culture-related facilities increased. These findings indicate significant pandemic-induced alterations in the mobility patterns of senior citizens in Seoul, highlighting shifts towards safer, more accessible environments.