• Title, Summary, Keyword: Driving algorithm

Search Result 979, Processing Time 0.037 seconds

Path Planning for the Shortest Driving Time Considering UGV Driving Characteristic and Driving Time and Its Driving Algorithm (무인 주행 차량의 주행 특성과 주행 시간을 고려한 경로 생성 및 주행 알고리즘)

  • Noh, Chi-Beom;Kim, Min-Ho;Lee, Min-Cheol
    • The Journal of Korea Robotics Society
    • /
    • v.8 no.1
    • /
    • pp.43-50
    • /
    • 2013
  • $A^*$ algorithm is a global path generation algorithm, and typically create a path using only the distance information. Therefore along the path, a moving vehicle is usually not be considered by driving characteristics. Deceleration at the corner is one of the driving characteristics of the vehicle. In this paper, considering this characteristic, a new evaluation function based path algorithm is proposed to decrease the number of driving path corner, in order to reduce the driving cost, such as driving time, fuel consumption and so on. Also the potential field method is applied for driving of UGV, which is robust against static and dynamic obstacle environment during following the generated path of the mobile robot under. The driving time and path following test was occurred by experiments based on a pseudo UGV, mobile robot in downscaled UGV's maximum and driving speed in corner. The experiment results were confirmed that the driving time by the proposed algorithm was decreased comparing with the results from $A^*$ algorithm.

Driving Pattern Recognition Algorithm using Neural Network for Vehicle Driving Control (차량 주행제어를 위한 신경회로망을 사용한 주행패턴 인식 알고리즘)

  • Jeon, Soon-Il;Cho, Sung-Tae;Park, Jin-Ho;Park, Yeong-Il;Lee, Jang-Moo
    • Proceedings of the KSME Conference
    • /
    • /
    • pp.505-510
    • /
    • 2000
  • Vehicle performances such as fuel consumption and catalyst-out emissions are affected by a driving pattern, which is defined as a driving cycle with the grade in this study. We developed an algorithm to recognize a current driving pattern by using a neural network. And this algorithm can be used in adapting the driving control strategy to the recognized driving pattern. First, we classified the general driving patterns into 6 representative driving patterns, which are composed of 3 urban driving patterns, 2 suburban driving patterns and 1 expressway driving pattern. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, relative duration spent at stop, average acceleration and average grade are chosen to characterize the driving patterns. Second, we used a neural network (especially the Hamming network) to decide which representative driving pattern is closest to the current driving pattern by comparing the inner products between them. And before calculating inner product, each element of the current and representative driving patterns is transformed into 1 and -1 array as to 4 levels. In the end, we simulated the driving pattern recognition algorithm in a temporary pattern composed of 6 representative driving patterns and, verified the reliable recognition performance.

  • PDF

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
    • /
    • v.27 no.7
    • /
    • pp.1146-1151
    • /
    • 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.

A New Washout Algorithm for Reappearance of Driving Perception of Simulator (운전 시뮬레이터의 주행감각 재현을 위한 새로운 가속도 모의 수법 알고리즘 개발)

  • 유기성;이민철
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.10 no.6
    • /
    • pp.519-528
    • /
    • 2004
  • For reappearance of driving perception in a driving simulator, a washout algorithm is required. This algorithm can reappear the vehicle driving motions within workspace of the driving simulator. However classical washout algorithm contains several problems such as selection of order, cut-off frequency of filters, generation of wrong motion cues by characteristics of filters, etc. In order to overcome these problems, this paper proposes a new washout algorithm which gives more accurate sensations to drivers. The algorithm consists of an artificial inclination of the motion plate and human perception model with band pass filter and dead zone. As a result of this study, the motion of a real car could be reappeared satisfactorily in the driving simulator and the workspace of motion plate is restrained without scaling factor.

Development of a Safe Driving Management System (안전운전 관리시스템 개발)

  • Cho, Jun-Hee;Lee, Woon-Sung
    • Transactions of the Korean Society of Automotive Engineers
    • /
    • v.15 no.1
    • /
    • pp.71-77
    • /
    • 2007
  • Dangerous driving is a major cause of traffic accidents in Korea. It becomes more serious for commercial vehicles due to higher fatality rates. The Safe Driving Management System (SDMS), developed in this research, is a comprehensive solution that monitors and stores driving conditions of vehicles, detects dangerous driving situations, and analyzes the results in real time. The Safe Driving Management System consists of a vehicle movement information controller, a dangerous driving detection algorithm and a vehicle movement data report and analysis program. The dangerous driving detection algorithm detects and classifies dangerous driving conditions into representative cases such as sudden acceleration, sudden braking, sudden lane change, and sudden turning. Both computer simulation and vehicle test have been conducted to develop and verify the algorithm. The Safe Driving Management System has been implemented on commercial buses to verify its reliability and objectivity. It is expected that the system can contribute to prevention of traffic accidents, systemization of safe driving management and reduction of commercial vehicle operation costs.

Driving Algorithm for Contact-free Linear Actuator (비접촉 선형 구동기를 위한 구동 알고리즘)

  • 이상헌;백윤수
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • /
    • pp.1034-1037
    • /
    • 2003
  • Recently in the field of precision positioning device, the contact-free actuators are gaining focuses with their outstanding performances by eliminating mechanical frictions. Th is paper is about the driving algorithm for contact-free linear actuator. The proposed driving algorithm has similar structure of drives of switched reluctance motor and reduces the normal forces and force ripple. The simulation and experiment are executed to verify the proposed method.

  • PDF

Observer Based Estimation of Driving Resistance Load for Vehicle Longitudinal Motion Control

  • Kim, Duk-Ho;Shin, Byung-Kwan;Kyongsu Yi;Lee, Kyo-Il
    • 제어로봇시스템학회:학술대회논문집
    • /
    • /
    • pp.185-188
    • /
    • 1999
  • An estimation algorithm for vehicle driving load has been proposed in this paper. Driving load is an important factor in a vehicle's longitudinal motion control. An approach using an observer is introduced to estimate driving load based on inexpensive RPM sensors currently being used in production vehicles. Also, a torque estimation technique using nonlinear characteristic functions has been incorporated in this estimation algorithm. Using a nonlinear full vehicle simulation model, we study the effect of the driving load on longitudinal vehicle motion, and the performance of the estimation algorithm has been evaluated. The proposed estimation algorithm has good performance and robustness over uncertainties in the system parameters. An accurate estimate of the driving load can be very helpful in the development of advance vehicle control systems such as intelligent cruise control systems, CW/CA systems and smooth shift control systems.

  • PDF

A Development of Parallel Type Hybrid Drivetrain System for Transit Bus Part 3 : Optimal Driving Control Algorithm (버스용 병렬형 하이브리드 동력전달계의 개발(III) 제 3 편;최적 주행 제어 알고리즘)

  • 조한상;이장무;박영일
    • Transactions of the Korean Society of Automotive Engineers
    • /
    • v.7 no.6
    • /
    • pp.182-197
    • /
    • 1999
  • Described in this paper is an optimal driving control algorithm which focused on the improvement of fuel economy and the minimization of pollutant emissions in the parallel type hybrid drivertrain system for transit bus. For the energy balance among components such as engine, induction machine and buttery, the algorithm for power split ration determine is proposed. When it is implemented in the hybrid electric control unit(HECU) , using the sub-optimal method and the approximate technique , it is possible to save the memory , to shorten the calculation time, and to achieve the efficient driving actually. A Shift strategy for automated manual transmission is the other side of the driving control algorithm. It enables to select the optimal gear by using several shift maps which were predefined from the proposed method in this paper, As a results of driving simulation, it is proved that these algorithms make the hybrid drivetrain system to reduce fuel consumption and emissions considerably and to have the ability to the efficient use of battery.

  • PDF

Synchronous Position Control of Pneumatic Cylinder Driving Apparatus (공기압 실린더 구동 장치의 위치 동기 제어)

  • Jang, Ji-Seong
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.28 no.9
    • /
    • pp.1415-1421
    • /
    • 2004
  • In this study, a position synchronous control algorithm applied to two-axes pneumatic cylinder driving apparatus is proposed. The position synchronous control algorithm is composed of position controller and synchronous controller. The position controller is designed to minimize the effect of several nonlinear characteristics peculiar to the pneumatic cylinder driving apparatus on position control performance. The synchronous controller is designed to reduce the synchronous error. The effectiveness of the proposed control algorithm is proved by experimental results.

A Human-Centered Control Algorithm for Personalized Autonomous Driving based on Integration of Inverse Time-To-Collision and Time Headway (자율주행 개인화를 위한 역 충돌시간 및 차두시간 융합 기반 인간중심 제어 알고리즘 개발)

  • Oh, Kwang-Seok
    • Journal of the Korea Convergence Society
    • /
    • v.9 no.10
    • /
    • pp.249-255
    • /
    • 2018
  • This paper presents a human-centered control algorithm for personalized autonomous driving based on the integration of inverse time-to-collision and time headway. In order to minimize the sense of difference between driver and autonomous driving, the human-centered control technology is required. Driving characteristics in case that vehicle drives with the preceding vehicle have been analyzed and reflected to the longitudinal control algorithm. The driving characteristics such as acceleration, inverse time-to-collision, time headway have been analyzed for longitudinal control. The control algorithm proposed in this study has been constructed on Matlab/Simulink environment and the performance evaluation has been conducted by using actual driving data.