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

Longitudinal velocity control design with error tolerance strategy for autonomous vehicle

This work serves as the proof of concept of an autonomous vehicle prototype developed by Moovita and Universiti Teknologi Malaysia. For a dependable driverless vehicle maneuver, it requires a stable velocity controller to allow for the desired longitudinal motion navigation. Thus, a multi-level longitudinal velocity control is proposed as part of the motion guidance strategy. The higher level formulates the desired braking and torque actuation relative to the obtained reference generator information, while the lower level aids the vehicle to actuate the actuators. The focus will be on the higher-level velocity control design, where (i) it is expected to yield alternate actuation between braking and gas, and (ii) to prevent the sudden increase in actuation and yield a more-human like behavior. An error tolerance strategy is included in the controller design to achieve this. The controller design is then validated on a varied speed real-time experiment as a proof of concept. Results show the proposed controller is able to provide the desirable navigation for controlled AV navigation in a predefined environment

Feasible, robust and reliable automation and control for autonomous systems

The global market for autonomous robotics platforms has grown rapidly due to the advent of drones, mobile robots, and driverless cars, while the mass media coverage examining the progress of robotics and autonomous systems field is widespread [...

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 obstacles edge

Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver

Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs )

Effect of road profile on normal force generated on electric vehicle

Electric vehicles are gaining popularity for its various advantages including environmental aspects. However, the vehicles are still susceptible to accidents due to factors such as uneven road surface. Thus, this paper focus on the effect of road profile on the suspension and normal force produced on an electric vehicle. A simple vehicle model is designed in MATLAB Simulink using longitudinal vehicle dynamic model and passive suspension of the quarter-car model. The vehicle is accelerated on the road while introducing an uneven road surface. The result obtained shows an increase of the vehicle suspension deflection and normal force produced. A vehicle moving on three varying hump height is shown to produce a minor disturbance on the total normal force of the vehicle. However, the effect is significant enough on the normal force on each tire

The vibration effects of a two in-wheel electric vehicle towards the human brain

The human biodynamic and vehicle models are often modelled separately in order to understand the impact of vibration on the human itself and vehicle ride comfort, respectively. Nonetheless, several studies have recently combined both models into a single system to investigate the dynamic response and ride comfort during travelling. In this study, five degrees of freedom (5DOF) human biodynamic model is incorporated with a two in-wheel electric car model to correlate the impact of vibration on a tire towards the human brain. The model is analysed through MATLAB simulation with a car travelling at a speed of 10 km/h. It could be observed from the present investigation that the proposed model is able to highlight a significant impact of the brain to the skull when the car is on the move or in cornering mode

Piecewise Trajectory Replanner for Highway Collision Avoidance Systems with Safe-Distance Based Threat Assessment Strategy and Nonlinear Model Predictive Control

This paper proposes an emergency Trajectory Replanner (TR) for collision avoidance (CA) which works based on a Safe-Distance Based Threat Assessment Strategy (SDTA). The contribution of this work is the design of a piecewise-kinematic based TR, where it replans the path by avoiding the invisible rectangular region created by SDTA. The TR performance is measured by assessing its ability to yield a maneuverable path for lane change and lane keeping navigations of the host vehicle. The reliability of the TR is evaluated in multi-scenario computational simulations. In addition, the TR is expected to provide a reliable replanned path during the increased nonlinearity of high-speed collisions. For this reason, Nonlinear Model Predictive Control (NMPC) is adopted into the design to track the replanned trajectory via an active front steering and braking actuations. For path tracking strategy, comparisons with benchmark controllers are done to analyze NMPC’s reliability as multi-actuators nonlinear controller of the architecture to the CA performance in high-speed scenario. To reduce the complexity of the NMPC formulation, Move Blocking strategy is incorporated into the control design. Results show that the CA system performed well in emergency situations, where the vehicle successfully replanned the obstacle avoidance trajectory, produced dependable lane change and lane keeping navigations, and at the same time no side-collision with the obstacle’s edges occurred. Moreover, the multi-actuators and nonlinear features of NMPC as the PT strategy gave a better tracking performance in high-speed CA scenario. Assimilation of Move Blocking strategy into NMPC formulation lessened the computational burden of NMPC. The system is proven to provide reliable replanned trajectories and preventing multi-scenario collision risks while maintaining the safe distance and time constraints