• Title/Summary/Keyword: Intelligent Vehicles

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An Analysis on the Prevention Effects of Forward and Chain Collision based on Vehicle-to-Vehicle Communication (차량 간 통신 기반 전방추돌 및 연쇄추돌 방지 효과 분석)

  • Jung, Sung-Dae;Kim, Tae-Oh;Lee, Sang-Sun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.10 no.4
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    • pp.36-43
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    • 2011
  • The forward collision of vehicles in high speed can cause a chain collisions and high fatality rate. Most of the forward collisions are caused by insufficient braking distance due to detection time of driver and safe distance. Also, accumulated detection time of driver is cause of chain collisions after the forward collision. The FVCWS prevents the forward collision by maintaining the safety distance inter-vehicle and reducing detection time of driver. However the FVCWS can cause chain collisions because the system that interacts only forward vehicle has accumulated detection time of driver. In this paper, we analyze forward and chain collisions of normal vehicles and FVCWS vehicles on static traveling scenario. And then, we analyze and compare V2V based FVCWS with them after explaining the system. The V2V FVCWS reduces detection time of driver alike FVCWS as well as remove accumulated detection time of driver by broadcasting emergence message to backward vehicles at the same time. Therefore, the system decrease possibility of forward and chain collisions. All backward normal vehicles and 3~4 backward FVCWS vehicles have possibility of forward and chain collisions in result of analysis. However V2V FVCWS vehicles almost do not chain collisions in the result.

Study on Improvement of Connected Vehicles Interface Board and Transition Algorithm of Digital Traffic Signal Controller for Autonomous Vehicles and C-ITS (자율주행차 및 C-ITS 지원을 위한 디지털 교통신호 제어기의 신호정보연계장치 및 전이 알고리즘 개선 연구)

  • Ko, Sejin;Choi, Eunjin;Gho, Gwang-Yong;Han, Eum;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.2
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    • pp.15-29
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    • 2021
  • The signal intersection is the most challenging space for autonomous vehicles. To promote the safe driving of autonomous vehicles on urban roads with traffic signals, autonomous vehicles need to receive traffic signal information from infrastructure through V2I communication. Thus, a protocol for providing traffic signal information was added to the standard traffic signal controller specification of the National Police Agency. On the other hand, there are technical limitations when applying this to digital traffic signal controllers because the protocols are defined mainly for analog traffic signal controllers. Therefore, this study proposes developing a signal information linkage module to provide traffic signal information from a digital traffic signal controller to an autonomous vehicle and an algorithm improvement method that can provide accurate traffic signal information at the time of traffic signal transition.

Spatiotemporal Traffic Density Estimation Based on Low Frequency ADAS Probe Data on Freeway (표본 ADAS 차두거리 기반 연속류 시공간적 교통밀도 추정)

  • Lim, Donghyun;Ko, Eunjeong;Seo, Younghoon;Kim, Hyungjoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.208-221
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    • 2020
  • The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.

A Study on the Development of Driving Risk Assessment Model for Autonomous Vehicles Using Fuzzy-AHP (퍼지 AHP를 이용한 자율주행차량의 운행 위험도 평가 모델 개발 연구)

  • Siwon Kim;Jaekyung Kwon;Jaeseong Hwang;Sangsoo Lee;Choul ki Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.1
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    • pp.192-207
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    • 2023
  • Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

Design and Performance Analysis of u-TSMVPN for Intelligent Transportation Systems (지능형 교통시스템을 위한 u-TSMVPN의 설계와 성능분석)

  • Jeon, Hae-Nam;Jeong, Jongpil
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.9
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    • pp.32-45
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    • 2013
  • Globally, intelligent vehicles and telematics research and development through the integration of IT technology in the vehicle are significant increasing. Real-time data communication for intelligent transportation system (ITS) is very important. It collects real-time data from the vehicle and provides the information collected from ITS center. We propose an effective and secure communication scheme for these communication procedures. In particular, our proposed SIP-based MVPN reduces signaling cost and has many advantages in security aspects. In addition, our proposed scheme performs the mobility management applying NEMO (Network Mobility) for the communication between the vehicles. In other words, we propose an ITS communication mechanism of SIP-based mobile VPN and V2V NEMO. Finally, our performance analysis show that the ITS of SIP-based MVPN is significantly reducing the handoff signaling cost.

A Nonlinear Information Filter for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment

  • Kim, Yong-Shik;Hong, Keum-Shik
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1669-1674
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    • 2004
  • In this paper, a nonlinear information filter (IF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, a nonlinear IF is used in place of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

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An IMM Algorithm for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment

  • Kim, Yong-Shik;Hong, Keum-Shik
    • International Journal of Control, Automation, and Systems
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    • v.2 no.3
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    • pp.310-318
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    • 2004
  • In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

A development of Intelligent Parking Control System Using Sensor-based on Arduino

  • LIM, Myung-Jae;JUNG, Dong-Kun;KWON, Young-Man
    • Korean Journal of Artificial Intelligence
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    • v.9 no.2
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    • pp.29-34
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    • 2021
  • In this paper, for efficient parking control, in an Arduino environment, an intelligent parking control prototype was implemented to provide parking control and parking guidance information using HC-SR2O4 and RC522. The main elements of intelligent parking control are vehicle recognition sensors, parking control facilities, and integrated operating software. Whether the vehicle is parked on the parking surface may be confirmed through sensor or intelligent camera image analysis. Parking control equipment products include parking guidance and parking available display devices, vehicle number recognition cameras, and intelligent parking assistance systems. This paper applies and implements ultrasonic sensors and RFID concepts based on Arduino, recognizes registered vehicles, and displays empty spaces. When a vehicle enters a parking space to handle this function, the automatic parking management system distinguishes the registered vehicle from the external vehicle through the RC522 sensor. In addition, after checking whether the parking slot is empty, the HC-SR204 sensor is displayed through the LED so that the driver can visually check it. RFID is designed to check the parking status of the server in real time and provide the driver with optimal route service to the parking slot.