• Title/Summary/Keyword: Intelligent Vehicles

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User Experience Factors in Connected Car Infotainment Applications : Focusing on Text Mining Analysis in the Android Auto Reviews (커넥티드카 인포테인먼트 애플리케이션의 사용자 경험 요인 : 안드로이드 오토 리뷰의 텍스트마이닝 분석을 중심으로)

  • Jung Yong Kim;Su-Eun Bae;Junho Choi
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.4
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    • pp.211-225
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    • 2023
  • In the future, infotainment systems are expected to play a pivotal role in mobility ecosystems connecting users and vehicles. This study draws user-experience factors from reviews of Android Auto, a car infotainment application, and analyzes factors that affect satisfaction. The user-experience factors of infotainment have been redefined based on previous studies. To analyze actual user-experience factors, topics are obtained, applied, and interpreted from user discourse through topic modeling. Sentiment analysis and logistic regression are used to determine positive and negative user-experience factors that affect satisfaction. Results of the empirical analysis show that Ease of Use and Understandability are factors that have the greatest impact on satisfaction, and Flexibility, Safety, and Playfulness are factors that have the most critical effect on dissatisfaction. Therefore, this paper suggests ways to improve the satisfaction level of the infotainment system, and establishes a strategy accordingly.

An Approach for the Estimation of Mixture Distribution Parameters Using EM Algorithm (복합확률분포의 파라메타 추정을 위한 EM 알고리즘의 적용 연구)

  • Daeyoung Shim;SangGu Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.4
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    • pp.35-47
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    • 2023
  • Various single probability distributions have been used to represent time headway distributions. However, it has often been difficult to explain the time headway distribution as a single probability distribution on site. This study used the EM algorithm, which is one of the maximum likelihood estimations, for the parameters of combined mixture distributions with a certain relationship between two normal distributions for the time headway of vehicles. The time headway distribution of vehicle arrival is difficult to represent well with previously known single probability distributions. But as a result of this analysis, it can be represented by estimating the parameters of the mixture probability distribution using the EM algorithm. The result of a goodness-of-fit test was statistically significant at a significance level of 1%, which proves the reliability of parameter estimation of the mixture probability distribution using the EM algorithm.

An Optimal Route Algorithm for Automated Vehicle in Monitoring Road Infrastructure (도로 인프라 모니터링을 위한 자율주행 차량 최적경로 알고리즘)

  • Kyuok Kim;SunA Cho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.1
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    • pp.265-275
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    • 2023
  • The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.

Scenario-based Future Infantry Brigade Information Distribution Capability Analysis (시나리오 기반의 미래 보병여단 정보유통능력 분석 연구)

  • Junseob Kim;Sangjun Park;Yiju You;Yongchul Kim
    • Convergence Security Journal
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    • v.23 no.1
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    • pp.139-145
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    • 2023
  • The ROK Army is promoting cutting-edge, future-oriented military development such as a mobile, intelligent, and hyper-connected Army TIGER system. The future infantry brigade plans to increase mobility with squad-level tactical vehicles to enable combat in multi-domain operations and to deploy various weapon systems such as surveillance and reconnaissance drones. In addition, it will be developed into an intelligent unit that transmits and receives data collected through the weapon system through a hyper-connected network. Accordingly, the future infantry brigade will transmit and receive more data. However, the Army's tactical information communication system has limitations in operating as a tactical communication system for future units, such as low transmission speed and bandwidth and restrictions on communication support. Therefore, in this paper, the information distribution capability of the future infantry brigade is presented through the offensive operation scenario and M&S.

Analysis of the Effects of the Truck Platooning Using a Meta-analysis (메타분석을 이용한 화물차 군집주행의 효과 분석)

  • Kim, Yejin;Jeong, Harim;Ko, Woori;Park, Joong-gyu;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.76-90
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    • 2022
  • The platooning refers to a form in which one or more following vehicles along the path of the leading vehicle(directly driven by the driver) drive in one platoon using V2V, V2I communication and vehicle-mounted sensor. Platooning has emerged in line with the increasing demand for cargo volume and advanced transportation logistics systems, and is expected to have effects such as increasing capacity, reducing labor costs, and reducing fuel consumption. However, compared to general passenger cars, research on autonomous driving of trucks and verification of their effects are insufficient. Therefore, in this study, meta-analysis was conducted on the theme of the effect of truck platooning, and the results of existing studies related to platooning effects were integrated into one reliable, generalized, and objective summary estimate. In conclusion, it was analyzed that the introduction of truck platooning would have an effect of 13.93% increase in capacity, 38.76% decrease in conflict, and 8.13% decrease in fuel consumption.

Evaluation of LDM (Local Dynamic Map) Service Based on a Role in Cooperative Autonomous Driving with a Road (자율협력주행을 위한 역할 기반 동적정보 서비스 평가 방법)

  • Roh, Chang-Gyun;Kim, Hyoungsoo;Im, I-Jeong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.258-272
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    • 2022
  • The technology implementation method was diversified into an 'autonomous cooperative driving' method to overcome the limitations of a stand-alone autonomous vehicle with vehicle sensor-based autonomous driving. The autonomous cooperative driving method involves exchanging information between roadside infrastructure and autonomous vehicles. In this process, the concept of dynamic information (LDM), a target of cooperation, was established. But, evaluation methods and standards for dynamic information have not been established. Therefore, this study, a dynamic information evaluation method based on information on pedestrians within the moving objects. In addition, autonomous cooperative driving was demonstrated, and dynamic information was also verified through the evaluation method. The significance of this study is that it established the dynamic information evaluation methodology for autonomous cooperative driving for the first time. Based on this, this study is expected to contribute to the application of safe autonomous cooperative driving technology to the field.

Algorithm for Freight Transportation Performance Estimation on Expressway Using TCS and WIM Data (TCS 및 WIM 데이터를 활용한 고속도로 화물수송실적 산정 알고리즘 개발)

  • Youjeong Kang;Jungyeol Hong;Yoonhyuk Choi
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.116-130
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    • 2023
  • Expressways play pivotal roles in cargo transportation because of their superior accessibility and mobility compared to rail and air. On the other hand, there is a limit to the accurate calculation of cargo transportation performance using existing highways owing to the mixture of vehicle types and difficulty in identifying cargo loads of individual cargo vehicles. This paper presents an algorithm for calculating more reliable cargo transportation performance using big data. The traffic performance (veh·km/day) was derived using the data collected from Toll Collecting System. The average tolerance weight for each vehicle type and the cargo load unit (ton/unit) considering it was calculated using vehicle specification information data and high-speed and low-speed axis data. This study calculated the cargo transportation performance by section and type using various online integrated highway data and presented a method for calculating the transportation performance by linking open business offices and private highways.

Method of Multiple Scenario Transformation and Simulation Based Evaluation for Automated Vehicle Assessment (자율주행자동차 평가를 위한 다중 시나리오 변환과 시뮬레이션 기반 평가 방법)

  • Donghyo Kang;Inyoung Kim;Seong-Woo Cho;Ilsoo Yun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.230-245
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    • 2023
  • The importance of evaluating the safety of Automated Vehicles (AV) is increasing with the advances in autonomous driving technology. Accordingly, an evaluation scenario that defines in advance the situations AV may face while driving is being used to conduct efficient stability evaluation. On the other hand, the single scenarios currently used in conventional evaluations address limited situations within short segments. As a result, there are limitations in evaluating continuous situations that occur on real roads. Therefore, this study developed a set of multiple scenarios that allow for continuous evaluation across entire sections of roads with diverse geometric structures to assess the safety of AV. In particular, the conditions for connecting individual scenarios were defined, and a methodology was proposed for developing concrete multiple scenarios based on the scenario evaluation procedure of the PEGASUS project. Furthermore, a simulation was performed to validate the practicality of these multiple scenarios.

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 the Visiting Areas Classification of Cargo Vehicles Using Dynamic Clustering Method (화물차량의 방문시설 공간설정 방법론 연구)

  • Bum Chul Cho;Eun A Cho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.141-156
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    • 2023
  • This study aims to improve understanding of freight movement, crucial for logistics facility investment and policy making. It addresses the limitations of traditional freight truck traffic data, aggregated only at city and county levels, by developing a new methodology. This method uses trip chain data for more detailed, facility-level analysis of freight truck movements. It employs DTG (Digital Tachograph) data to identify individual truck visit locations and creates H3 system-based polygons to represent these visits spatially. The study also involves an algorithm to dynamically determine the optimal spatial resolution of these polygons. Tested nationally, the approach resulted in polygons with 81.26% spatial fit and 14.8% error rate, offering insights into freight characteristics and enabling clustering based on traffic chain characteristics of freight trucks and visited facility types.