TY - GEN
T1 - Path Planning Design for Vehicle Driving Assist Systems
AU - Hsieh, Ping Jui
AU - Chen, Guan Yan
AU - Chiang, I. Chieh
AU - Perng, Jau Woei
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - In recent years, brand new vehicles equipped with muti-driving assist systems have been more and more popular. As a result, we propose a path planning design for muti-vehicle driving assist systems that enable vehicle adjust speed and traveling direction according to different road sections by itself. The overall system can be divided into two layers, one is decision layer and the other is control layer. In decision layer, reference route which built by high accuracy real time kinematic differential positioning system is necessary. Then, reference route would be separated into bending and straight sections. After that, desired speed and steering angle can be obtained by kinematics equations and position node of reference route. In control layer, actuators, such as throttle, braking paddle, and steering wheel, are driven by fuzzy logic controller to reach desired speed and steering angle from decision layer. The overall system is implemented on an electric golf car which as a testing platform. The experimental results show that the proposed system integrates kinematic and human experience to fulfill above functions.
AB - In recent years, brand new vehicles equipped with muti-driving assist systems have been more and more popular. As a result, we propose a path planning design for muti-vehicle driving assist systems that enable vehicle adjust speed and traveling direction according to different road sections by itself. The overall system can be divided into two layers, one is decision layer and the other is control layer. In decision layer, reference route which built by high accuracy real time kinematic differential positioning system is necessary. Then, reference route would be separated into bending and straight sections. After that, desired speed and steering angle can be obtained by kinematics equations and position node of reference route. In control layer, actuators, such as throttle, braking paddle, and steering wheel, are driven by fuzzy logic controller to reach desired speed and steering angle from decision layer. The overall system is implemented on an electric golf car which as a testing platform. The experimental results show that the proposed system integrates kinematic and human experience to fulfill above functions.
UR - http://www.scopus.com/inward/record.url?scp=85057623971&partnerID=8YFLogxK
U2 - 10.1109/ICSSE.2018.8520136
DO - 10.1109/ICSSE.2018.8520136
M3 - Conference contribution
AN - SCOPUS:85057623971
T3 - 2018 International Conference on System Science and Engineering, ICSSE 2018
BT - 2018 International Conference on System Science and Engineering, ICSSE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on System Science and Engineering, ICSSE 2018
Y2 - 28 June 2018 through 30 June 2018
ER -