• Journal of Information Processing Systems
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• v.5 no.4
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• pp.237-242
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• 2009

The classical vehicle routing problem (VRP) can be extended by including customers who want to send goods to the depot. This type of VRP is called the vehicle routing problem with pickups and deliveries (VRPPD). This study proposes a novel way to solve VRPPD by introducing a two-phase heuristic routing algorithm which consists of a clustering phase and uses the geometrical center of a cluster and route establishment phase by applying a two-way search of each route after applying the TSP algorithm on each route. Experimental results show that the suggested algorithm can generate better initial solutions for more computer-intensive meta-heuristics than other existing methods such as the giant-tour-based partitioning method or the insertion-based method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.744-750
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• 2010

To segment instances of vehicle classes in a sparse stereo-matching data set, this paper presents an algorithm for clustering based on DP (Dynamic Programming). The algorithm is agglomerative: it begins with each element in the set as a separate cluster and merges them into successively larger clusters according to similarity of two clusters. Here, similarity is formulated as a cost function of DP. The proposed algorithm is proven to be effective by experiments performed on various images acquired by a moving vehicle.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.59-68
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• 2022

We propose the vehicle maintenance support system to alarm consumable replacement reminders to the vehicle owner. Since the delayed replacement of the consumables makes the condition of the vehicle worse, it is crucial to replace consumables in a recommended period. The vehicle maintenance support system alarms the replacement time, which is set by the vehicle owner, based on the mileage of the installed vehicle. It integrates speed information acquired from the Controller Area Network interface for communication between Electronic Control Unit and instrument panel, exposed at the On Board Diagnostics-II port, to calculate the vehicle mileage. By this, there is no additional wiring required for the system. We verify the system has only 0.28% error by comparing the mileage on the system with the instrument cluster on the vehicle. It automatically enters low-power mode consuming 15mW, which is a negligible amount for the typical conditions of the car, to prevent the vehicle battery from discharging when the ignition is off.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.132-145
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• 2022

This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.590-592
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• 2018

Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2025-2035
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• 2014

The read range of UHF mobile readers can be extended by a booster for mobile RFID readers (BoMR). But in an environment where multiple BoMRs are installed, the read success rate may be decreased due to signal interference. This paper proposes three arbitration methods based on interference estimation with the purpose of enhancing the read success rate. A central arbitration server manages global information in centralized arbitration method (CAM) without broadcast/multicast communication facility. In fully distributed arbitration method (FDAM), all the arbitration messages are broadcasted from a BoMR to every BoMR, and each BoMR decides with broadcasted global information. Events in FDAM are serialized naturally with broadcasted messages. Cluster Distributed Arbitration Method (CDAM) forms clusters with multicasted BoMRs and a selected BoMR acts as an arbiter in the cluster. Such effects as lengthened read range, improved the read success rates of readers can be obtained by the proposed methods without any hardware modification. In order to evaluate the arbitration methods, the RFID system is modeled by using the DEVS formalism and simulated by using the DEVSim++.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.194-210
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• 2022

The user-centered EV charging infrastructure construction policy the government is aiming for can increase convenience for electric vehicle users and bring new electric vehicle users into the market. This study was conducted to provide an in-depth understanding of the charging behaviors of actual electric vehicle users, which can be used as basic information for the electric vehicle charging infrastructure. Based on charging diary data collected for a week, the charging of electric vehicles was analyzed on a daily and weekly basis, and sequence analysis and latent class analysis were used. As a result, five daily charging profiles and four weekly charging profiles were identified, which are expected to contribute to revitalizing the electric vehicle market by providing key information for decision-making by potential electric vehicle users as well for establishing user-centered charging infrastructure policies in the future.

• IE interfaces
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• v.21 no.1
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• pp.43-50
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• 2008

Understanding consumers' latent desires for product form has now become a critical issue in product design. Accordingly, product development processes is rapidly changing from product-oriented development to user-centered development. Driver visibility is considered as an important element of driving posture packaging in automobile interior design. This study presents a systematic process for driver visibility analysis approached from affective engineering method that provides design variable selection and screening with respect to the image/impression element of the human visibility. Also, the analysis of front visibility, often called the feeling of "openness", in motor vehicle interior design, is selected and practiced a case study using the systematic process proposed in this study. Twenty six participants evaluated the feeling of openness for thirty motor vehicles following the perceived scale of affective design factors. The results showed that variables such as the height of head lining, the height of cluster housing, the gradient of windshield and the volume of A-pillar were the critical design variables which affect the feeling of openness in a motor vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1462-1477
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• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.271-272
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• 2021

본 논문에서는 Gazebo 시뮬레이터 기반 UAV 군집 시뮬레이션 구현 및 비행 고도 계층화를 구현한 결과를 보인다. Gazebo 시뮬레이션과 Autopilot Program인 Pixhawk4 SITL(Software In The Loop)을 이용하여 UAV를 시뮬레이터에 생성한 뒤 사전에 정의된 Mission에 대한 정보에 따라 비행이 되도록 구현하였다. 또한, Gazebo 시뮬레이터의 Box Object를 이용하여 UAV의 비행 고도를 시각적으로 계층화하여 표현하였다.