• Title/Summary/Keyword: Intelligent Vehicle

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Evaluation of Technical Feasibility for Vehicle Classification Using Inductive Loop Detectors on Freeways (고속도로 루프검지기를 이용한 차종분류 기법 평가)

  • Park, Joon-Hyeong;Kim, Tae-Jin;Oh, Cheol
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.1
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    • pp.9-21
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    • 2009
  • This study presents a useful heuristic algorithm to classify vehicle classes using vehicle length information, which is extracted from inductive loop vehicle signatures. A high-speed scanning equipment was used to extract more detailed change of inductance magnitude for individual vehicles. Vehicle detection time and individual vehicle speeds were used to derive vehicle length information that is an input of the proposed algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm performance more systematically. It is expected that the proposed method would be useful for obtaining vehicle classification information from wide-spread existing loop infrastructure.

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INTELLIGENT CONTROL STRATEGY FOR A MOBILE VEHICLE WITH NEURCOMPUTER

  • Sugisaka, Masanori;Wang, Xin;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.815-818
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    • 1997
  • In this paper, an intelligent control strategy for a mobile vehicle, based on the technology of the artificial neural network in a Neurocomputer, is presented. The mobile vehicle learned recognizing and driving knowledge by a neurocomputer. Moment Invariants computation was used to extract the shape of objects. The technologies of both neurocomputer and Neumann-type computer are applied into the control system, and make the mobile vehicle be capable of tracking designated objects and avoiding obstacles.

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Speed and Steering Control of Autonomous Vehicle Using Neural Network (신경회로망을 이용한 자율주행차량의 속도 및 조향제어)

  • 임영철;류영재;김의선;김태곤
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.274-281
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    • 1998
  • This paper describes a visual control of autonomous vehicle using neural network. Visual control for road-following of autonomous vehicle is based on road image from camera. Road points on image are inputs of controller and vehicle speed and steering angle are outputs of controller using neural network. Simulation study confirmed the visual control of road-following using neural network. For experimental test, autonomous electric vehicle is designed and driving test is realized

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Driver Adaptive Control Algorithm for Intelligent Vehicle (운전자 주행 특성 파라미터를 고려한 지능화 차량의 적응 제어)

  • Min, Suk-Ki;Yi, Kyong-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.7
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    • pp.1146-1151
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    • 2003
  • In this paper, results of an analysis of driving behavior characteristics and a driver-adaptive control algorithm for adaptive cruise control systems have been described. The analysis has been performed based on real-world driving data. The vehicle longitudinal control algorithm developed in our previous research has been extended based on the analysis to incorporate the driving characteristics of the human drivers into the control algorithm and to achieve natural vehicle behavior of the adaptive cruise controlled vehicle that would feel comfortable to the human driver. A driving characteristic parameters estimation algorithm has been developed. The driving characteristics parameters of a human driver have been estimated during manual driving using the recursive least-square algorithm and then the estimated ones have been used in the controller adaptation. The vehicle following characteristics of the adaptive cruise control vehicles with and without the driving behavior parameter estimation algorithm have been compared to those of the manual driving. It has been shown that the vehicle following behavior of the controlled vehicle with the adaptive control algorithm is quite close to that of the human controlled vehicles. Therefore, it can be expected that the more natural and more comfortable vehicle behavior would be achieved by the use of the driver adaptive cruise control algorithm.

Development of a coordinated control algorithm using steering torque overlay and differential braking for rear-side collision avoidance (측후방 충돌 회피를 위한 조향 보조 토크 및 차등 제동 분배 제어 알고리즘 개발)

  • Lee, Junyung;Kim, Dongwook;Yi, Kyongsu;Yoo, Hyunjae;Chong, Hyokjin;Ko, Bongchul
    • Journal of Auto-vehicle Safety Association
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    • v.5 no.2
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    • pp.24-31
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    • 2013
  • This paper describes a coordinated control algorithm for rear-side collision avoidance. In order to assist driver actively and increase driver's safety, the proposed coordinated control algorithm is designed to combine lateral control using a steering torque overlay by Motor Driven Power Steering (MDPS) and differential braking by Vehicle Stability Control (VSC). The main objective of a combined control strategy is twofold. The one is to prevent the collision between the subject vehicle and approaching vehicle in the adjacent lanes. The other is to limit actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort. In order to achieve these goals, the Lyapunov theory and LMI optimization methods has been employed. The proposed coordinated control algorithm for rear-side collision avoidance has been evaluated via simulation using CarSim and MATLAB/Simulink.

LMI-BASED $H_{\infty}$ LATERAL CONTROL OF AN AUTONOMUS VEHICLE BY LOOK-AHEAD SENSING

  • Kim, C.S.;Kim, S.Y.;Ryu, J.H.;Lee, M.H.
    • International Journal of Automotive Technology
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    • v.7 no.5
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    • pp.609-618
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    • 2006
  • This paper presents the lateral control of an autonomous vehicle by using a look-ahead sensing system. In look-ahead sensing by an absolute positioning system, a reference lane, constructed by straight lanes or circular lanes, was switched by a segment switching algorithm. To cope with sensor noise and modeling uncertainty, a robust LMI-based $H_{\infty}$ lateral controller was designed by the feedback of lateral offset and yaw angle error at the vehicle look-ahead. In order to verify the safety and the performance of lateral control, a scaled-down vehicle was developed and the location of the vehicle was detected by using an ultrasonic local positioning system. In the mechatronic scaled-down vehicle, the lateral model and parameters are verified and estimated by a J-turn test. For the lane change and reference lane tracking, the lateral controllers are used experimentally. The experimental results show that the $H_{\infty}$ controller is robust and has better performance compared with look-down sensing.

Development of an Intelligent Unmanned Vehicle Control System (지능형 무인자동차 제어시스템 개발)

  • Kim, Yoon-Gu;Lee, Ki-Dong
    • IEMEK Journal of Embedded Systems and Applications
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    • v.3 no.3
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    • pp.126-135
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    • 2008
  • The development of an unmanned vehicle basically requires the robust and reliable performance of major functions which include global localization, lane detection, obstacle avoidance, path planning, etc. The implementation of major functional subsystems are possible by integrating and fusing data acquired from various sensory systems such as GPS, vision, ultrasonic sensor, encoder, and electric compass. This paper focuses on implementing the functional subsystems, which are designed and developed by a graphical programming tool, NI LabVIEW, and also verifying the autonomous navigation and remote control of the unmanned vehicle.

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Estimation of vehicle cornering stiffness via GPS/INS

  • Park, Gun-Hong;Chang, Yu-Shin;Ryu, Jae-Heon;Jeong, Seung-Gweon;Song, Hyo-Shin;Park, Seok-Hyun;Lee, Chun-Han;Hong, Sin-Pyo;Lee, Man-Hyung
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1706-1709
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    • 2003
  • This paper demonstrates a unique method for measuring vehicle states such as body sideslip angle and tire sideslip angle using Global Positioning System(GPS) velocity information in conjunction with other sensors. A method for integrating Inertial Navigation System (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented, and the method can be used to estimate the tire cornering stiffness. The experimental results for the GPS velocity-based sideslip angle measurement. From the experimental results, it can be concluded that the proposed method has an advantage for future implementation in a vehicle safety system.

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An Efficient Anonymous Authentication Scheme with Secure Communication in Intelligent Vehicular Ad-hoc Networks

  • Zhang, Xiaojun;Mu, Liming;Zhao, Jie;Xu, Chunxiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.3280-3298
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    • 2019
  • Vehicular ad-hoc networks (VANETs) have become increasingly significant in intelligent transportation systems, they play a great role in improving traffic safety and efficiency. In the deployment of intelligent VANETs, intelligent vehicles can efficiently exchange important or urgent traffic information and make driving decisions. Meanwhile, secure data communication and vehicle's identity privacy have been highlighted. To cope with these security issues, in this paper, we construct an efficient anonymous authentication scheme with secure communication in intelligent VANETs. Combing the ElGamal encryption technique with a modified Schnorr signature technique, the proposed scheme provides secure anonymous authentication process for encrypted message in the vehicle-to-infrastructure communication model, and achieves identity privacy, forward security, and reply attack resistance simultaneously. Moreover, except the trusted authority (TA), any outside entity cannot trace the real identity of an intelligent vehicle. The proposed scheme is designed on an identity-based system, which can remove the costs of establishing public key infrastructure (PKI) and certificates management. Compared with existing authentication schemes, the proposed scheme is much more practical in intelligent VANETs.