• Title/Summary/Keyword: Intelligent car

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Formal Model of Extended Reinforcement Learning (E-RL) System (확장된 강화학습 시스템의 정형모델)

  • Jeon, Do Yeong;Song, Myeong Ho;Kim, Soo Dong
    • Journal of Internet Computing and Services
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    • v.22 no.4
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    • pp.13-28
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    • 2021
  • Reinforcement Learning (RL) is a machine learning algorithm that repeat the closed-loop process that agents perform actions specified by the policy, the action is evaluated with a reward function, and the policy gets updated accordingly. The key benefit of RL is the ability to optimze the policy with action evaluation. Hence, it can effectively be applied to developing advanced intelligent systems and autonomous systems. Conventional RL incoporates a single policy, a reward function, and relatively simple policy update, and hence its utilization was limited. In this paper, we propose an extended RL model that considers multiple instances of RL elements. We define a formal model of the key elements and their computing model of the extended RL. Then, we propose design methods for applying to system development. As a case stud of applying the proposed formal model and the design methods, we present the design and implementation of an advanced car navigator system that guides multiple cars to reaching their destinations efficiently.

Emergency vehicle priority signal system based on deep learning using acoustic data (음향 데이터를 활용한 딥러닝 기반 긴급차량 우선 신호 시스템)

  • Lee, SoYeon;Jang, Jae Won;Kim, Dae-Young
    • Journal of Platform Technology
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    • v.9 no.3
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    • pp.44-51
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    • 2021
  • In general, golden time refers to the most important time in the initial response to accidents such as saving lives or extinguishing fires. The golden time varies from disaster to disaster, but is aimed at five minutes in terms of fire and first aid. However, for the actual site, the average dispatch time for ambulances is 9 minutes and the average transfer time is 17.6 minutes, which is quite large compared to the golden time. There are various causes for this delay, but the main cause is traffic jams. In order to solve the problem, the government has established emergency car concession obligations and secured golden time to prioritize ambulances in places with the highest accident rate, but it is not a solution in rush hour when traffic is increasing rapidly. Therefore, this paper proposed a deep learning-based emergency vehicle priority signal system using collected sound data by installing sound sensors on traffic lights and conducted an experiment to classify frequency signals that differ depending on the distance of the emergency vehicle.

Real-Time Traffic Information and Road Sign Recognitions of Circumstance on Expressway for Vehicles in C-ITS Environments (C-ITS 환경에서 차량의 고속도로 주행 시 주변 환경 인지를 위한 실시간 교통정보 및 안내 표지판 인식)

  • Im, Changjae;Kim, Daewon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.1
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    • pp.55-69
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    • 2017
  • Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

The Road Reservation Scheme in Emergency Situation for Intelligent Transportation Systems (지능형 교통 시스템을 위한 긴급 상황에서의 도로 예약 방식)

  • Yoo, Jae-Bong;Park, Chan-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.11B
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    • pp.1346-1356
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    • 2011
  • Transportation has been playing important role in our society by providing for people, freight, and information. However, it cuts its own throat by causing car accidents, traffic congestion, and air pollution. The main cause of these problems is a noticeable growth in the number of vehicles. The easiest way to mitigate these problems is to build new road infrastructures unless resources such as time, money, and space are limited. Therefore, there is a need to manage the existing road infrastructures effectively and safely. In this paper, we propose a road reservation scheme that provides fast and safe response for emergency vehicles using ubiquitous sensor network. Our idea is to allow emergency vehicle to reserve a road on a freeway for arriving to the scene of the accident quickly and safely. We evaluate the performance by three reservation method (No, Hop, and Full) to show that emergency vehicles such as ambulances, fire trucks, or police cars can rapidly and safely reach their destination. Simulation results show that the average speed of road reservation is about 1.09 ~ 1.20 times faster than that of non-reservation at various flow rates. However, road reservation should consider the speed of the emergency vehicle and the road density of the emergency vehicle processing direction, as a result of Hop Reservation and Full Reservation performance comparison analysis. We confirm that road reservation can guarantee safe driving of emergency vehicles without reducing their speed and help to mitigate traffic congestion.

Reliability Analysis of VOC Data for Opinion Mining (오피니언 마이닝을 위한 VOC 데이타의 신뢰성 분석)

  • Kim, Dongwon;Yu, Song Jin
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.217-245
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    • 2016
  • The purpose of this study is to verify how 7 sentiment domains extracted through sentiment analysis from social media have an influence on business performance. It consists of three phases. In phase I, we constructed the sentiment lexicon after crawling 45,447 pieces of VOC (Voice of the Customer) on 26 auto companies from the car community and extracting the POS information and built a seven-sensitive domains. In phase II, in order to retain the reliability of experimental data, we examined auto-correlation analysis and PCA. In phase III, we investigated how 7 domains impact on the market share of three major (GM, FCA, and VOLKSWAGEN) auto companies by using linear regression analysis. The findings from the auto-correlation analysis proved auto-correlation and the sequence of the sentiments, and the results from PCA reported the 7 sentiments connected with positivity, negativity and neutrality. As a result of linear regression analysis on model 1, we indentified that the sentimental factors have a significant influence on the actual market share. In particular, not only posotive and negative sentiment domains, but neutral sentiment had significantly impacted on auto market share. As we apply the availability of data to the market, and take advantage of auto-correlation of the market-related information and the sentiment, the findings will be a huge contribution to other researches on sentiment analysis as well as actual business performances in various ways.

A Study on GIS Component Classification considering Functional/Non-Functional Elements (기능적/비기능적 요소를 고려한 GIS 컴포넌트 분류에 관한 연구)

  • Jo, Yun-Won;Jo, Myung-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.5 no.3
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    • pp.77-86
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    • 2002
  • Recently software industry in GIS(geographic information system) becomes an interesting issue by performing a large scale of national GIS application development as well as even small unit of FMS(facility management system). Also, there exist many cases to combine GIS with various business domains such as MIS(marketing information system), CNS(car navigation system) and ITS(intelligent transportation system). In this situation, in order to develop an efficient and useful GIS application for a short term, there must be a deep consideration of not only developing GIS component but also managing GIS component. In fact, even though there exist many certain components having high reusability, excellent interoperability and good quality, their reusability may be reduced because of their difficulty to access in a certain repository. Therefore, it is important to classify components having common characteristic based on their particular rule with reflecting their functionality and non-functionality before cataloging them. Here, there are two non-functional classification categories discussed such as GIS content-dependent metadata and GIS content-independent metadata. This cataloged components will help application developers to select easily their desired components. Moreover, new components may be easily producted by modifying and combining previous components. Finally, the original goal of all this effort can be defined through obtaining high reusability and interoperability of GIS component.

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VLC Based Positioning Scheme in Vehicle-to-Infra(V2I) Environment (차량-인프라간 가시광 통신 기반 측위 기술)

  • Kim, Byung Wook;Song, Deok-Weon;Lee, Ji-Hwan;Jung, Sung-Yoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.3
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    • pp.588-594
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    • 2015
  • Although GPS technology for location positioning system has been widely used, it is difficult to be used in intelligent transport systems, due to the large positioning error and limited area for receiving radio signals. Thanks to the rapid development of LED technology, LED lights become popular in many applications. Especially, visible light communications (VLC) has raised a lot of interests because of the simultaneous functioning of LED illumination and communication. Recent studies on positioning system using VLC mainly focused on indoor environments and still difficult to satisfy positioning accuracy and simple implementation simultaneously. In this paper, we propose a positioning system based on VLC using the coordinate information of LEDs installed on the road infrastructure. Extracting the LED signal, obtained through VLC, from the easily accessible camera image, it is possible to estimate the position of the car on the road. Simulation results show that the proposed scheme can achieve a high positioning accuracy of 1 m when large number of pixels is utilized and the distance from the LED light is close.

VANET Privacy Assurance Architecture Design (VANET 프라이버시 보장 아키텍처 설계)

  • Park, Su-min;Hong, Man-pyo;Shon, Tae-shik;Kwak, Jin
    • Journal of Internet Computing and Services
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    • v.17 no.6
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    • pp.81-91
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    • 2016
  • VANET is one of the most developed technologies many people have considered a technology for the next generation. It basically utilizes the wireless technology and it can be used for measuring the speed of the vehicle, the location and even traffic control. With sharing those information, VANET can offer Cooperative ITS which can make a solution for a variety of traffic issues. In this way, safety for drivers, efficiency and mobility can be increased with VANET but data between vehicles or between vehicle and infrastructure are included with private information. Therefore alternatives are necessary to secure privacy. If there is no alternative for privacy, it can not only cause some problems about identification information but also it allows attackers to get location tracking and makes a target. Besides, people's lives or property can be dangerous because of sending wrong information or forgery. In addition to this, it is possible to be information stealing by attacker's impersonation or private information exposure through eavesdropping in communication environment. Therefore, in this paper we propose Privacy Assurance Architecture for VANET to ensure privacy from these threats.

Robust Motorbike License Plate Detection and Recognition using Image Warping based on YOLOv2 (YOLOv2 기반의 영상워핑을 이용한 강인한 오토바이 번호판 검출 및 인식)

  • Dang, Xuan-Truong;Kim, Eung-Tae
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.713-725
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    • 2019
  • Automatic License Plate Recognition (ALPR) is a technology required for many applications such as Intelligent Transportation Systems and Video Surveillance Systems. Most of the studies have studied were about the detection and recognition of license plates on cars, and there is very little about detecting and recognizing license plates on motorbikes. In the case of a car, the license plate is located at the front or rear center of the vehicle and is a straight or slightly sloped license plate. Also, the background of the license plate is mainly monochromatic, and license plate detection and recognition process is less complicated. However since the motorbike is parked by using a kickstand, it is inclined at various angles when parked, so the process of recognizing characters on the motorbike license plate is more complicated. In this paper, we have developed a 2-stage YOLOv2 algorithm to detect the area of a license plate after detection of a motorbike area in order to improve the recognition accuracy of license plate for motorbike data set parked at various angles. In order to increase the detection rate, the size and number of the anchor boxes were adjusted according to the characteristics of the motorbike and license plate. Image warping algorithms were applied after detecting tilted license plates. As a result of simulating the license plate character recognition process, the proposed method had the recognition rate of license plate of 80.23% compared to the recognition rate of the conventional method(YOLOv2 without image warping) of 47.74%. Therefore, the proposed method can increase the recognition of tilted motorbike license plate character by using the adjustment of anchor boxes and the image warping which fit the motorbike license plate.

Edge to Edge Model and Delay Performance Evaluation for Autonomous Driving (자율 주행을 위한 Edge to Edge 모델 및 지연 성능 평가)

  • Cho, Moon Ki;Bae, Kyoung Yul
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.191-207
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    • 2021
  • Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.