The comparison respond of braking torque control between PID and SMC controller for electric powered wheelchair descending on slope condition

During descending on a slope, the speed of Electric Powered Wheelchair (EPW) tends to changed rapidly. Normally, most EPW is provided with mechanical braking system which transfers human pulling force of the lever creating friction at the tire. However, the task is difficult for the users are elderly or paralyses. However, even for normal user with good strength, in fear condition they tend to give sudden braking which leads to tire locking up and skidding, eventually EPW unstable. These problems will cause accident and injuries to the users if speed does not properly control. In this paper, the automated braking torque control method was proposed in EPW as alternative to solve this problem and increase the mobility and stability especially during descending on slope in other to help the user of the EPW as their daily transportation. In this research, Proportional-Integral-Derivative and Sliding Mode Control controller are compared to determine the best response for torque braking control. The rapid change of speed can be controlled by the braking torque using proposed controllers based on the desired constant speed set by the control designer. Moreover, the sudden braking that caused tire to lock up and skid can be avoided. Furthermore, result from SMC shows this controller have good time respond to maintain the speed based on desired value when descending at slope condition by controlling the braking torque compared to the PID controller

Investigation of the combination of kinematic path planning and artificial potential field path planning with PI controller for autonomous emergency braking pedestrian (AEB-P) System

Autonomous Emergency Braking Pedestrian (AEB-P) is a fundamental capacity of the advanced driver assistance system (ADAS) to maintain a distance and avoid a collision. The fatality of pedestrian in traffic accident as well as near-miss accidents are the most frequent type of accidents in Malaysia as the improvisation of AEB-P system are obligatory. To generate optimum vehicle deceleration from the path planner in the presence of a pedestrian in front of the vehicle, an Artificial Potential Field (APF) path planner with a kinematic path planner is proposed in this research. The kinematic path planner will produce maximum deceleration for the vehicle, 8 m/s2, as the vehicle violates the threshold. The value is combining with the APF value to fetch to the PI controller. Thus, the AEB-P system was designed considering the pedestrian walked in front of the vehicle at 4.32 km/h and vehicle travelled at 60 km/h, dry and wet road surface condition, time for Front Collision Warning (FCW), and full braking was included for the limit APF is developed. The PI controller will tune the deceleration using its variable on dry road surface (P = 0.003, I = 5) and on wet road surface (P = 0.003, I = 8500). The host vehicle starts to give warning signal at 37.29 m and experience full braking at 21.3 m when the vehicle travel on both types of surfaces. The vehicle manages to stop from hitting the pedestrian at 2.21 and 1.5 m on the dry and wet road surface. The proposed AEB-P architecture can avoid the collision with pedestrian as the vehicle manage to stop from hitting the obstacle at a comfortable distance

Investigation of brake pad wear impact on autonomous emergency braking pedestrian performance on wet road conditions

This study presents an investigation of autonomous emergency braking pedestrian (AEB-P) system performance during harsh braking on wet road pavement. The system was designed to consider a pedestrian walking in front of the host vehicle. The performance of the AEB-P system would degrade immediately as the pads on the brakes become worn, and the vehicle continues to brake on a wet road surface. The vehicle conditional artificial potential field (VC-APF) is an innovative approach for motion planning in the AEB-P introduced in this work. The simulation was performed to explore the impact of brake pad degradation on VC-APF effectiveness on wet road pavement. The first evaluation involved a test to evaluate the effectiveness of the risk assessment in the AEB-P system when encountering a moving obstacle (pedestrian). The second test evaluated VC-APF performance, for instance, the vehicle's safety distance when the vehicle performed hard braking at 0.4, 0.35, and 0.24 brake pad friction coefficients. The third evaluation focused on the vehicle’s speed behavior during deceleration at various brake pad friction coefficients. The simulation results showed that while braking at 0.4 and 0.35 brake pad friction coefficients, the vehicle maintained a minimum safety distance of 1.5 m and 0.69 m from a pedestrian on wet road pavement, respectively. However, the brake pad friction coefficient of 0.24 failed to prevent the vehicle from crashing. The findings indicate that an exhausted brake pad reduces the vehicle's safety

A Novel Triangular-Based Estimation Technique for Bezier Curve Control Points Generation on Autonomous Vehicle Path Planning at the Roundabout Intersection

Path planning plays a major role in autonomous vehicle navigation. Among different kinds of intersections, roundabouts are far more difficult to plot a course than other intersections due to their special design. Different curve fitting methods such as circles, clothoid curves, Bezier curves are utilized for path planning inside a roundabout. Among those Bezier curves are widely used as they can generate a possible number of paths. However, the major drawback when adopting a Bezier curve is locating its control points. Control points need to be placed correctly for the path to generate. Roundabouts have varying shapes and sizes, there is no one-size-fits-all strategy for locating the control points in a roundabout. Moreover, the circulating path of a roundabout is generally formed based on the radius of the circular path, but this method cannot be applied in all roundabouts since the roundabout can have variable shapes depending on the available space. Therefore, this paper introduces a new method called the triangular-based point selection approach for locating the control points for a Bezier curve traversing a path. The triangular-based point selection approach is used to find points on the road to calculate the control points of a Bezier curve passing through these points. The circular path is likewise created using Bezier curve allowing the path to follow the contour of the roundabout. The proposed method is demonstrated in an oval-shaped roundabout and tested using a vehicle model also the proposed path generation algorithm is compared with other path planning methods

An Investigation of Classical Model Predictive Controller Path Tracking Performance of a Two-Wheel and Four-Wheel Steering Vehicle

Studies on self-driving vehicles have become a trend in recent years, and many systems have been developed to enable autonomous manoeuvre. Various methods have been used to improve path-tracking algorithms which increase vehicle performance, including tracking accuracy and stability. Path tracking is one of the primary problems for autonomous vehicles where the vehicle deviates from target paths, which leads to unnecessary counter-correction. Conventional front wheel steering is unable to satisfy the manoeuvre with a high lateral acceleration since the front steering angle is limited in accurately responding to vehicle dynamics. Moreover, the characteristics of front wheel steering vehicles affect handling stability due to the fact that the turning radius is larger than the vehicle itself. This disadvantageous can compromise safety during under-steer and over-steer situations. The main objective of this preliminary study is to investigate the performance of a four-wheel steering system (4WS) in path tracking for autonomous vehicles using a classical model predictive controller (MPC). Conventional two-wheel steering (2WS) tracking performance following the desired driving system with the same MPC controller is compared with 4WS vehicles. The driving system is developed using Driving Scenario Designer to extract the desired yaw angle and lateral position for controller references constructed in Matlab Simulink. Fixed MPC constraint, prediction, control horizon, yaw angle and lateral position weights were used to compare the performance between 2WS and 4WS vehicles. The simulation results show that 4WS is three times better than 2WS vehicles in tracking predetermined paths. 4WS vehicle show 74.55% better performance in lateral position tracking and 68.75% better performance in trailing predetermined yaw angle value. The simulation data from the preliminary study will be used as a guideline to develop an advanced controller of 4WS vehicles

Object tracking for autonomous vehicle using YOLO V3

Accuracy and performance of an object detection model have always been the main requirements for an object tracking system. In this project, the performance of machine learning based object detection using YOLO v3 technique will be investigated. Two models were provided where one model is trained using online Common Objects in Contact (COCO) dataset only, and the other model is trained with additional images from Universiti Malaysia Pahang (UMP) with several different locations dataset. The performance of the trained models were evaluated using mean Average Precision (mAP), and precision techniques. The model with highest precision was selected to be implemented on actual road test. The results show that the model 2 has the highest precision and was able to detect every class of objects. Each output box had displayed the class and the distance to the objects from the RGBD camera of the vehicle. It is observed that the first model that was trained to perform the mAP value of 90.2% and a performance of 0.484 precision. For the second model, it can be seen that the accuracy of the detections are higher than that of model 1. Therefore, model 2 has a better performance with a value of 0.596 precision

Performance of Photogrammetry-Based Makeshift 3D Scanning System for Geometrical Object in Reverse Engineering

A three-dimension (3D) scanner is one of the important tools for digital reproduction of physical objects in reverse engineering. In some cases, a makeshift 3D scanner is needed immediately, such as for emergency spare parts reproduction. Thus, this research aims to investigate the feasibility of a low-cost makeshift 3D scanner using a mobile phone and the photogrammetry method in reconstructing digital 3D models of geometrical objects. A focus is given to the dimension accuracy of the reconstructed 3D models, which have been reproduced using images taken by a mobile phone, in comparison with the actual dimension of the scanned test pieces. To do so, four types of actual geometrical test pieces with dimension from 5 to 175 mm had been fabricated using CNC machine. 3D models of each test pieces had been developed using the photogrammetry method and compared with those developed using an industrial-grade high-end 3D scanner. It was found that mobile photogrammetry achieved an average accuracy of 97.2%, with minimum and maximum values of 83.3% and 99.9%, respectively. Geometrical dimensions less than 10 mm tend to have lower accuracy, while it was the opposite for dimensions over 150 mm. Furthermore, the scanning limit for either method was found to be a surface with a small tilting angle (less than 3 degrees). Nevertheless, photogrammetry method in combination with a mobile phone has the potential to be utilized as an alternative of a makeshift 3D scanning system with sufficient accuracy using commonly available tools

Performance of Photogrammetry-Based Makeshift 3D Scanning System for Geometrical Object in Reverse Engineering

A three-dimension (3D) scanner is one of the important tools for digital reproduction of physical objects in reverse engineering. In some cases, a makeshift 3D scanner is needed immediately, such as for emergency spare parts reproduction. Thus, this research aims to investigate the feasibility of a low-cost makeshift 3D scanner using a mobile phone and the photogrammetry method in reconstructing digital 3D models of geometrical objects. A focus is given to the dimension accuracy of the reconstructed 3D models, which have been reproduced using images taken by a mobile phone, in comparison with the actual dimension of the scanned test pieces. To do so, four types of actual geometrical test pieces with dimension from 5 to 175 mm had been fabricated using CNC machine. 3D models of each test pieces had been developed using the photogrammetry method and compared with those developed using an industrial-grade high-end 3D scanner. It was found that mobile photogrammetry achieved an average accuracy of 97.2%, with minimum and maximum values of 83.3% and 99.9%, respectively. Geometrical dimensions less than 10 mm tend to have lower accuracy, while it was the opposite for dimensions over 150 mm. Furthermore, the scanning limit for either method was found to be a surface with a small tilting angle (less than 3 degrees). Nevertheless, photogrammetry method in combination with a mobile phone has the potential to be utilized as an alternative of a makeshift 3D scanning system with sufficient accuracy using commonly available tools

3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm

3D LiDAR-based object detection during autonomous vehicle navigation is a trending field in autonomous vehicle research and development. As 3D LiDAR is resistant to light interference while capable of capturing detailed 3D spatial structures of the detected objects, it is the main perception sensor for autonomous vehicles. With its improved accessibility in the recent years, the advent of deep learning had allowed feature learning from sparse 3D point clouds. Hence, this leads a plethora of methods in object detection for 3D sparse point clouds. In this research, an extensive experiment was conducted using various 3D LiDAR object detections for various forms like pillar-form, point-form and voxel-form onto multiple point cloud data sets captured using Robotic Operating System (ROS). Based on experiments conducted, pillar-form point cloud data is suitable for dense point clouds, while voxel-form is optimal for both indoors and outdoors environment

Comparison of braking performance between mechanical and dynamic braking for Electric Powered Wheelchair

Braking is the necessary system need to install as the safety feature for moving transportation. Using the mechanical braking only as primary braking system in Electric Transportation (ET) is insufficient due to some issues such as low strength users hand gripping and abruptly tire locking during braking especially on wet surface condition. In this paper, the performance between mechanical and electrical braking which is by using dynamic braking concept is proposed to enhance the braking performance of Electric Powered Wheelchair (EPW). The experiments were conducted during descending on the slope under wet and dry pavements. From the results of slip ratio, the slipping time between mechanical and dynamic braking in dry pavement is recorded 0.9 seconds and 0.7 seconds respectively. Meanwhile, it is observed that tire is fully locked-up for mechanical braking under the wet surface. However, by using the dynamic braking, the wheel does not lock-up and the slipping time was recorded 1.4 seconds. It can be considered that, mechanical and dynamic braking give their own merit. The high braking torque from mechanical braking is suitable to use under the dry pavement for the short stopping distance. The other sides, braking under the wet pavement, dynamic braking is more efficient compare to the mechanical braking in term of short slipping time and does not cause tire to lockup while braking