Today’s intelligent self-driving vehicles alongside technology development are more believable. One of the intelligent features of self-driving cars is autonomous parking which has been specifically considered in industry and academic research areas. This paper focuses on the autonomous parallel parking. First, the vehicle kinematics modeling by considering Ackermann angle calculation has been thoroughly explained and then the desired path by satisfying spatial conditions and its proportional steering angle is extracted. Autonomous parking scenario has been defined based on two phases of forward and backward motions. Accordingly, the desired training data includes steering angle and vehicle motion feedbacks (x, y, φ) that are utilized for designing intelligent controller. The proposed control system has two levels: upper and lower level. The former is a supervisory controller which switches between phases while the latter controls the vehicle based on received feedbacks from sensors in each phase. In this research adaptive-network-based fuzzy inference system (ANFIS) based on fuzzy c-means clustering (FCM) is employed to model the expert driver as an intelligent controller in parking maneuver. In this structure, FCM is used to systematically create the fuzzy membership functions and rule base for ANFIS. The performance of the proposed control algorithm is verified by defining an accuracy index. The simulation results in three different constant speeds indicate the value of accuracy index and jerk of controller output signals remains in an acceptable band.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Intelligent Parallel Parking Using Adaptive Neuro-Fuzzy Inference System Based on Fuzzy C-Means Clustering Algorithm


    Additional title:

    Sae Technical Papers



    Conference:

    Automotive Technical Papers ; 2017



    Publication date :

    2018-09-12




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Prediction of Automotive Ride Performance Using Adaptive Neuro-Fuzzy Inference System and Fuzzy Clustering

    Shi, Tianze / Chen, Shuming / Wang, Dengfeng | British Library Conference Proceedings | 2015


    Prediction of Automotive Ride Performance Using Adaptive Neuro-Fuzzy Inference System and Fuzzy Clustering

    Wang, Dengfeng / Chen, Shuming / Shi, Tianze | SAE Technical Papers | 2015


    Vehicle Classification Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

    Maurya, Akhilesh Kumar / Patel, Devesh Kumar | Springer Verlag | 2014


    Fault diagnosis using Neuro-Fuzzy Transductive Inference algorithm

    Bo Zhang, / Jianjun Luo, / Zhiqiu Chen, et al. | IEEE | 2008