Browsing by Author "Desoky, A."

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Implementation of Vision- Based Trajectory Control for Autonomous Vehicles.
(ASAT, 2017-04) Desoky, A.; Bayoumy, A.; Hassaan, G.
This paper demonstrates building, implementing, and developing a trajectory tracking control system based on computer vision for autonomous vehicles. The main goal of this system is to enforce the autonomous vehicle to be able to track road lane. This system includes a single digital camera, an embedded computer, and a microcontroller board. The digital camera is mounted at the top of the vehicle along its longitudinal axis. It captures a real-time sequence of images during vehicle motion. The captured images are then processed using Open-CV library for Python compiler over Linux operating system. These software packages are running on the embedded computer (Raspberry Pi 2) to obtain geometrical data of road lane. From this data, the observable errors can be determined. These errors are vehicle lateral offset and a heading error. Finally, a steering controller utilizes these errors in control law to compute the steering command. This command corrects offset and heading errors to ensure that the vehicle is in its way. The embedded computer then paths this command to Arduino microcontroller board to adjust the steering servomotor. The proposed implementation also demonstrates the integration between the embedded computer and microcontroller using Ethernet. During this work, a set of autonomous driving experiments is performed. Significant results are obtained that demonstrate the accuracy and robustness of the lane detection and control algorithms.
Modeling and Simulation of a Vision-Based Autonomous Vehicle.
(ASAT, 2017-04) Desoky, A.; Bayoumy, A; Hassaan, G.
This paper presents a comprehensive mathematical simulation for the trajectory of a vision-based autonomous vehicle during moving between lane lines of the structured road. The simulation accomplished by using MATLAB/Simulink software. This simulation mimics the existence of an actual digital camera by using a novel 3D-vision block to simulate the actual images that assumed to be provided by a digital camera connected to an embedded computer. The 3D-vision block uses mathematical equations, execution sequence and logical conditions to create a virtual captured image. So, this virtual image is then used to detect the lane in the front of the vehicle depending on the virtual camera position and its parameters. Inside simulation environment that based on the kinematic model of the vehicle and vision model, the controller has been designed that will be coded in the embedded computer. Several evaluations are shown and discussed about the lane detection and 3D vision simulation.