Trends in vehicle motion control for automated driving on public roads

In this paper, we describe how vehicle systems and the vehicle motion control are affected by automated driving on public roads. We describe the redundancy needed for a road vehicle to meet certain safety goals. The concept of system safety as well as system solutions to fault tolerant actuation of steering and braking and the associated fault tolerant power supply is described. Notably restriction of the operational domain in case of reduced capability of the driving automation system is discussed. Further we consider path tracking, state estimation of vehicle motion control required for automated driving as well as an example of a minimum risk manoeuver and redundant steering by means of differential braking. The steering by differential braking could offer heterogeneous or dissimilar redundancy that complements the redundancy of described fault tolerant steering systems for driving automation equipped vehicles. Finally, the important topic of verification of driving automation systems is addressed

Unmanned Ground Vehicles for Smart Farms

Forecasts of world population increases in the coming decades demand new production processes that are more efficient, safer, and less destructive to the environment. Industries are working to fulfill this mission by developing the smart factory concept. The agriculture world should follow industry leadership and develop approaches to implement the smart farm concept. One of the most vital elements that must be configured to meet the requirements of the new smart farms is the unmanned ground vehicles (UGV). Thus, this chapter focuses on the characteristics that the UGVs must have to function efficiently in this type of future farm. Two main approaches are discussed: automating conventional vehicles and developing specifically designed mobile platforms. The latter includes both wheeled and wheel-legged robots and an analysis of their adaptability to terrain and crops

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

Hybrid-learning-based classification and quantitative inference of driver braking intensity of an electrified vehicle

The recognition of driver's braking intensity is of great importance for advanced control and energy management for electric vehicles. In this paper, the braking intensity is classified into three levels based on novel hybrid unsupervised and supervised learning methods. First, instead of selecting threshold for each braking intensity level manually, an unsupervised Gaussian Mixture Model is used to cluster the braking events automatically with brake pressure. Then, a supervised Random Forest model is trained to classify the correct braking intensity levels with the state signals of vehicle and powertrain. To obtain a more efficient classifier, critical features are analyzed and selected. Moreover, beyond the acquisition of discrete braking intensity level, a novel continuous observation method is proposed based on Artificial Neural Networks to quantitative analyze and recognize the brake intensity using the prior determined features of vehicle states. Experimental data are collected in an electric vehicle under real-world driving scenarios. Finally, the classification and regression results of the proposed methods are evaluated and discussed. The results demonstrate the feasibility and accuracy of the proposed hybrid learning methods for braking intensity classification and quantitative recognition with various deceleration scenarios

Aggressive maneuver oriented robust actuator fault estimation of a 3-DOF helicopter prototype considering measurement noises

This paper presents a robust actuator fault estimation strategy design for a 3-DOF helicopter prototype which can be adapted to aggressive maneuvers. First, considering large pitch angle condition during flight, nonlinear coupling characteristic of the helicopter system is exploited. As the pitch angle can be measured in real time, a polytopic linear parameter-varying (LPV) model is developed for the helicopter system. Furthermore, considering measurement noises in the actual helicopter system, the dynamical model of helicopter system is modified accordingly. Then, based on the modified polytopic LPV model, a robust unknown input observer (UIO) is developed for the helicopter system to realize actuator fault estimation, in which both measurement noises and large pitch angle are considered. Robust performance of proposed fault estimation approach is guaranteed by using energy-to-energy strategy. And the observer gains are calculated by using linear matrix inequalities. Finally, based on a 3-DOF helicopter prototype, both simulations and experiments are conducted. The effects of measurement noises and large pitch angle on the fault estimation performance are sufficiently demonstrated. And effectiveness as well as advantages of the proposed observer is verified by using comparative analysis

Development of a Control System for an Urban Electric Vehicle Compatible with Autonomous Driving Features

As cities continue to grow, the roads only become more congested, leading drivers to spend more time commuting, while vehicle accidents continue to rise. The Mechatronics Vehicle Systems Laboratory has developed its own urban electric vehicle in an attempt to combat congestion, as well as pollution concerns in urban areas. The focus of these thesis is a fault tolerant control system to improve the robustness of the vehicle, as well as allow for future autonomous vehicle functions to be tested on it. The development of the control system began with deriving the requirements from the vehicle’s hardware, the goal of the project and foreseeable changes in the future. From there, the processors were selected, electronic control units were ordered, the vehicle’s necessarily electrical connections were completed, and the control software was deigned. Once every part of the project was completed, the control system was integrated, and testing was completed at the university. The goal of the control software was to allow the vehicle to be drivable if a motor, motor controller or steering actuator failed due to an electrical, mechanical or feedback fault. Due to the vehicle’s modular design it allowed other components to compensate for failures, while maintaining vehicle controllability and predictable vehicle dynamics. Furthermore, the control system allows for autonomous vehicle functions to be added and tested on the vehicle. This was tested through the addition of a lane following models, along with the control system’s path following function. The developed control system was shown to improve vehicle controllability when faults occurred, as well as allowed lane following to work effectively with the system structure and communication channels chosen. Overall, validating the design as well as allowing future mechanical designs or autonomous functions to be tested on the vehicle

Engineering assessment of current and future vehicle technologies: FMVSS no. 105 hydraulic and electric brake systems, FMVSS no. 135 passenger car brake systems; final report

This report provides a technical assessment of Federal Motor Vehicle Safety Standards (FMVSS) 105, Hydraulic and electric brake systems, and FMVSS 135, Passenger car brake systems. The review of these standards is part of a NHTSA’s Regulatory Review Plan to systematically examine all of the FMVSS. The primary thrust of the document is to address two questions: Do the current standards impede emerging technologies in passenger car and light/medium truck braking systems? Do the current standards require modification to adequately regulate emerging technologies? Emerging technologies are reviewed. Estimates of the extent and timing of their influence are made. It is concluded that the standards will not impede emerging technologies in the foreseeable future but could do so in the long term. The view is expressed that the approach of the current standards to ensuring adequate performance under partial-failure conditions may become ineffective as more, and more complex, automatic functions are added to automotive brake systems. A new approach may be required. Seventy-eight references are included in an annotated bibliography.National Highway Traffic Safety Administrationhttp://deepblue.lib.umich.edu/bitstream/2027.42/55414/1/99826.pd