Zuradzman Mohamad Razlan
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Preferred name
Zuradzman Mohamad Razlan
Official Name
Zuradzman, Mohamad Razlan
Alternative Name
Razlan, Zuradzman Mohamad
Zuradzman, M. R.
Razlan, Zuradzman M.
Main Affiliation
Scopus Author ID
55178487200
Researcher ID
AAU-4508-2020

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  • Publication
    Simulation studies of the hybrid human-fuzzy controller for path tracking of an autonomous vehicle
    ( 2021-01-01)
    Halin H.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Haris H.
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Zunaidi I.
    ;
    Wan Azani Wan Mustafa
    Human intelligence and experience help them in making a decision and recognize a pattern. This ability enables the driver to take action even in an unexpected situation. The hybrid integration between human intelligence/experience and machine controller able to improve the autonomous vehicle path tracking capability. The path tracking capability is the main concern of the autonomous vehicle. The Fuzzy developed from the experiment’s data. The experiments (human navigation experiments) used to gather the appropriate data from humans while controlling the buggy car. Data then use to develop the membership functions for inputs and output of the Fuzzy controller. The simulation uses to study the performance of the Fuzzy controller. The recorded path tracking error from the simulations for the right and left turn maneuver is 9 m and 7.5 m, respectively.
  • Publication
    Path tracking simulation of the buggy car by using Fuzzy information of the steering wheel
    ( 2020-01-01)
    Halin H.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Haris H.
    ;
    Zunaidi I.
    ;
    Bakar S.A.
    ;
    Zuradzman Mohamad Razlan
    ;
    Wan Azani Wan Mustafa
    The steering wheel control is the method used for the navigation of an autonomous vehicle. In order to control the autonomous vehicle, the steering wheel controller must be able to adapt as the road condition and surrounding environment can change abruptly. The existed autonomous system currently in the testing phase. The system still needs to improve because there is some report regarding an accident caused by the test autonomous vehicles. The aim of this research is to implement the human driving capability into the Fuzzy controller. One of the human capabilities is the ability to make a decision based on the current situation. The fuzzy system is developed based on human driving data while controlling a buggy car. The experiments used to collect data such as position, speed, heading and steering wheel angle. Data then use to develop the membership function for the fuzzy inputs and output. The simulation is performed in order to study the performance of the Fuzzy controller. The performance of the Fuzzy controller is satisfactory and can be improved. The maximum path tracking error recorded is 9 m and 7.5 m for right and left turn simulations.
  • Publication
    A Fusion of Sensors Information on Path Tracking for Autonomous Driving Control of An Electric Vehicle (EV)
    ( 2021-12-01)
    Haris H.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Halin H.
    ;
    Wan Azani Wan Mustafa
    ;
    Shahriman Abu Bakar
    ;
    Zuradzman Mohamad Razlan
    Depending on an intellectual level and experience, each human may make judgments and respond to situations autonomously. The driver is alerted and knows what to do in a specific circumstance while driving. This research aims to see how individuals act when driving an electric car down a predetermined path. An electric buggy car is built with equipment and sensors called an Electric Vehicle (EV) in experiments. Individuals who meet specified requirements are chosen to analyse their driving behaviours, and data is collected using various sensors. The speed, steering wheel angle, heading, and position of the buggy car are recorded throughout the human navigation trials. After the tests, data on human behaviour while driving straight and turning left and right are collected.
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