Tracking human movement in office environment using video processing

In this paper, we proposed an approach of multi-person movement tracking in office environment without any identity conflicts. Simple image processing with frame differentiation method is applied to identify multiple human motion. An Expert System is applied to predict next camera occurrence of the tracking human. The main objective of this work is to detect and track multi-human motion using single camera in more than a room in an office

Potential Field Based Motion Planning with Steering Control and DYC for ADAS

In this study, the development of motion planning and control for collision avoidance driver assistance systems is presented. A potential field approach has been used in formulating the collision avoidance algorithm based on predicted vehicle motion. Then, to realize the advanced driver assistance systems (ADAS) for collision avoidance, steering control system and direct yaw moment control (DYC) is designed to follow the desired vehicle motion. Performance evaluation is conducted in simulation environment in term of its performance in avoiding the obstacles. Simulation results show that the vehicle collision avoidance assistance systems can successfully complete the avoidance behavior without colliding

Driver`s Steering Behaviour Identification and Modelling in Near Rear-End collision

This paper studies and identifies driver`s steering manoeuvre behaviour in near rear-end collision. Time-To-Collision (TTC) is utilized in defining driver’s emergency threat assessment. The target scenario is set up under real experimental environment and the naturalistic data from the experiment are collected. Four normal drivers are employed for the experiment to perform the manoeuvre. Artificial Neural Network (ANN) is proposed to model the behaviour of the driver`s steering manoeuvre. The results show that all drivers manage to perform steering manoeuvre within the safe TTC region and the modelling results from ANN are reasonably positive. With further studies and improvements, this model would benefit to evaluate the driving reliability to enhance traffic safety and Intelligent Transportation System

Path Tracking on Autonomous Vehicle for Severe Maneuvre

Autonomous vehicle consists self-learning process consists recognizing environment, real time localization, path planning and motion tracking control. Path tracking is an important aspect on autonomous vehicle. The main purpose path tracking is the autonomous vehicle have an ability to follow the predefined path with zero steady state error. The non-linearity of the vehicle dynamic cause some difficulties in path tracking problems. This paper proposes a path tracking control for autonomous vehicle. The controller consists of a relationship between lateral error, longitudinal velocity, the heading error and the reference yaw rate. In addition, the yaw rate controller developed based on the vehicle and tyre model. The effectiveness of the proposed controller is demonstrated by a simulation

Pedestrian Detection using Triple Laser Range Finders

Pedestrian detection is one of the important features in autonomous ground vehicle (AGV). It ensures the capability for safety navigation in urban environment. Therefore, the detection accuracy became a crucial part which leads to implementation using Laser Range Finder (LRF) for better data representation. In this study, an improved laser configuration and fusion technique is introduced by implementation of triple LRFs in two layers with Pedestrian Data Analysis (PDA) to recognize multiple pedestrians. The PDA integrates various features from feature extraction process for all clusters and fusion of multiple layers for better recognition. The experiments were conducted in various occlusion scenarios such as intersection, closed-pedestrian and combine scenarios. The analysis of the laser fusion and PDA for all scenarios showed an improvement of detection where the pedestrians were represented by various detection categories which solve occlusion issues when low numberof laser data were obtained

Study on the potential application of electronic wedge brake for vehicle brake system

This paper presents a study of the potential application of an electronic wedge brake for vehicle brake system using human-in-the-loop simulation. Simulation was made in MATLAB Simulink software which interfaces an imaginary vehicle with a real time input from a human, such as throttle and brake input. The imaginary vehicle model that is used is a vehicle dynamic model that has been validated experimentally using an instrumented experimental vehicle. A validated electronic wedge brake actuator model was then used as the brake actuator model where a suitable control strategy, namely proportional-integral-derivative and proportional-integral controllers, was utilised as the force and gapping control respectively. To verify the effectiveness of the proposed actuator in a vehicle, the simulation results are compared with the results of human-in-the-loop simulation of a vehicle using a conventional hydraulic brake and the response of the experimental vehicle using the same dynamic test, namely the sudden braking test. The simulation results show that the proposed simulation method and actuator with appropriate controller strategy have similar behaviour to a hydraulic brake in terms of its capability to produce the desired braking force to reduce the speed and halt the vehicle. The outcomes from this study can be considered in design optimisation and implementation in a real vehicle

Path tracking controller of an autonomous armoured vehicle using modified Stanley controller optimized with particle swarm optimization

This study presents the development and optimization of a proposed path tracking controller for an autonomous armoured vehicle. A path tracking control is developed based on an established Stanley controller for autonomous vehicles. The basic controller is modified and applied on a non-linear, 7degree-of-freedom armoured vehicle model, and consists of various modules such as handling model, tire model, engine, and transmission model. The controller is then optimized using particle swarm optimization algorithm to select the optimum set of controller parameters. The main motivation of this study is that implementation of path tracking control on an autonomous armoured vehicle is still very limited and it is important to have a specific study on this field due to the different dynamics and properties of the armoured vehicle compared to normal passenger vehicles. Several road courses are considered and the performance of the developed controller in guiding the vehicle along these courses was compared against the original Stanley Controller. It was found that the optimized controller managed to improve the overall lateral error throughout the courses with 24–96% reduction in lateral error. Also, the optimization for the proposed controller was found to converge faster than its counterpart with up to 93% better solution

A Safe-Distance Based Threat Assessment with Geometrical Based Steering Control for Vehicle Collision Avoidance

This work proposes a vehicle collision avoidance strategy based on the usage of Geometrical Based Steering Controller. The algorithm is composed of these features : 1) Collision Detection strategy using safe distance threshold, 2) predicts the future trajectory of the vehicle in the occurrence of obstacle, 3) decision making prior to avoiding collision, 4) avoiding obstacles while ensuring the vehicle to return to its original path. The strategy used a nonlinear vehicle model with steering and braking input as the actuators that will react and avoid collisions. Simulation results depict the ability of the methods to avoid the potential collision while returning to its original path. The inclusion of the Threat Assessment Strategy ensures the hindrance of the vehicle from colliding with the obstacle's edg

Robust composite nonlinear feedback for nonlinear Steer-by-Wire vehicle’s Yaw control

Yaw control is a part of an Active Front Steering (AFS) system, which is used to improve vehicle manoeuvrability. Previously, it has been reported that the yaw rate tracking performance of a linear Steer-by-Wire (SBW) vehicle equipped with a Composite Nonlinear Feedback (CNF) controller and a Disturbance Observer (DOB) is robust with respect to side wind disturbance effects. This paper presents further investigation regarding the robustness of the combination between a CNF and a DOB in a nonlinear environment through a developed 7-DOF nonlinear SBW vehicle. Moreover, in contrast to previous studies, this paper also contributes in presenting the validation works of the proposed control system in a real-time situation using a Hardware-in-Loop (HIL) platform. Simulation and validation results show that the CNF and DOB managed to reduce the influence of the side wind disturbance in nonlinearities

Newly Developed Nonlinear Vehicle Model for an Active Anti-roll Bar System

This paper presents the development of a newly developed nonlinear vehicle model is used in the validation process of the vehicle model. The parameters chosen in a newly developed vehicle model is developed based on CARSIM vehicle model by using non-dominated sorting genetic algorithm version II (NSGA-II) optimization method. The ride comfort and handling performances have been one of the main objective to fulfil the expectation of customers in the vehicle development. Full nonlinear vehicle model which consists of ride, handling and Magic tyre subsystems has been derived and developed in MATLAB/Simulink. Then, optimum values of the full nonlinear vehicle parameters are investigated by using NSGA-II. The two objective functions are established based on RMS error between simulation and benchmark system. A stiffer suspension provides good stability and handling during manoeuvres while softer suspension gives better ride quality. The final results indicated that the newly developed nonlinear vehicle model is behaving accurately with input ride and manoeuvre. The outputs trend are successfully replicated