• Title/Summary/Keyword: Intelligent transportation

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A Study on Assessing User Preferences for Autonomous Driving Behavior Using a Driving Simulator (드라이빙 시뮬레이터를 활용한 자율주행 이용자 선호도 평가에 관한 연구)

  • Dohoon Kim;Sungkab Joo;Homin Choi;Junbeom Ryu
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.147-159
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    • 2023
  • In order to make autonomous vehicles more trustworthy, it is necessary to focus on the users of autonomous vehicles. By evaluating the preferences for driving behaviors of autonomous vehicles, we aim to identify driving behaviors that increase the acceptance of users in autonomous vehicles. We implemented two driving behaviors, aggressive and cautious, in a driving simulator and allowed users to experience them. Biometric data was collected during the ride, and pre- and post-riding surveys were conducted. Subjects were categorized into two groups based on their driving habits and analyzed against the collected biometric data. Both aggressive and cautious driving subjects preferred the cautious driving behavior of autonomous vehicles.

How to Set an Appropriate Scale of Traffic Analysis Zone for Estimating Travel Patterns of E-Scooter in Transporation Planning? (전동킥보드 통행분포모형 추정을 위한 적정 존단위 선정 연구)

  • Kyu hyuk Kim;Sang hoon Kim;Tai jin Song
    • 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.

A Path Generation Method Considering the Work Behavior of Operators for an Intelligent Excavator (운전자의 작업행태를 고려한 지능형 굴삭기의 이동경로 생성 방법)

  • Kim, Sung-Keun;Koo, Bonsang
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.4D
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    • pp.433-442
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    • 2010
  • Recent decrease in the availability of experienced skilled labor and a corresponding lack of new entrants has required the need for automating many of the construction equipment used in the construction industry. In particular, excavators are widely used throughout earthwork operations and automating its tasks enables work to be performed with higher productivity and safety. This paper introduces an optimal path generation method which is one of the core technologies required to make "Intelligent" excavators a reality. The method divides a given earthwork area into unit cells, identifies networks created by linking these cells, and identifies the optimal path an excavator should follow to minimize its total transportation costs. In addition, the method also accounts for drainage direction and path continuity to ensure that the generated path considers site specific conditions.

Intelligent Bridge Safety Prediction Edge System (지능형 교량 안전성 예측 엣지 시스템)

  • Jinhyo Park;Taejin Lee;Yong-Geun Hong;Joosang Youn
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.12
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    • pp.357-362
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    • 2023
  • Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

Study on the Enhancement of the Level of Service for the Pedestrian Queuing Area (보행자 점유공간 현행화 및 대기공간 서비스수준 산정을 위한 개선 연구)

  • Jungeun Yoon;Kyeongjin Lee;Hyoungsuk Jin;Heecheon You;Ilsoo Yun
    • 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.

Estimation of Driving Behavior Characteristics through Self-Reported-Based Driving Propensity (자기보고 기반 운전성향을 통한 주행행태 특성 추정 연구)

  • Sooncheon Hwang;Dongmin Lee
    • 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.

A Quantitative Analysis of Effects on Enhancing Bus Shelter Infrastructure: Focusing on Contingent Valuation Method by an User's Satisfaction Survey (버스정류장 시설 개선의 정량적 효과 분석: 이용자 만족도 조사 기반 CVM을 중심으로)

  • Kyuhyuk Kim;Myounggyu Kim;Nayeon Kim;Heesoo Kim;Tai-jin Song
    • 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.

Entity Embeddings for Enhancing Feasible and Diverse Population Synthesis in a Deep Generative Models (심층 생성모델 기반 합성인구 생성 성능 향상을 위한 개체 임베딩 분석연구)

  • Donghyun Kwon;Taeho Oh;Seungmo Yoo;Heechan Kang
    • 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.

Traffic Accidents Scenarios Based on Autonomous Vehicle Functional Safety Systems (자율주행차량 기능안전 시스템 기반 사고 시나리오 도출)

  • Heesoo Kim;Yongsik You;Hyorim Han;Min-je Cho;Tai-jin Song
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.264-283
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    • 2023
  • Unlike conventional vehicle traffic accidents, autonomous vehicles traffic accidents can be caused by various factors, including technical problems, the environment, and driver interaction. With the future advances in autonomous driving technology, new issues are expected to emerge in addition to the existing accident causes, and various scenario-based approaches are needed to respond to them. This study developed autonomous vehicle traffic accident scenarios by collecting autonomous driving accident reports, CA DMV collision reports, autonomous driving mode disengagement reports, and autonomous driving actual accident videos. The scenarios were derived based on the functional safety system failure modes of ISO 26262 and attempted to reflect the various issues of autonomous driving functions. The autonomous vehicle scenarios derived through this study are expected to play an essential role in preventing and preparing for various autonomous vehicle traffic accidents in the future and improving the safety of autonomous driving technology.

A Study on User Satisfaction Evaluation of Acceleration-Based Automated Driving Patterns (가속도 기반 자율주행 패턴에 대한 이용자 만족도 평가 연구)

  • Sooncheon Hwang;Dongmin Lee
    • 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.