A Systematic Survey of Control Techniques and Applications: From Autonomous Vehicles to Connected and Automated Vehicles

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger comfort, transportation efficiency, and energy saving. This survey attempts to provide a comprehensive and thorough overview of the current state of vehicle control technology, focusing on the evolution from vehicle state estimation and trajectory tracking control in AVs at the microscopic level to collaborative control in CAVs at the macroscopic level. First, this review starts with vehicle key state estimation, specifically vehicle sideslip angle, which is the most pivotal state for vehicle trajectory control, to discuss representative approaches. Then, we present symbolic vehicle trajectory tracking control approaches for AVs. On top of that, we further review the collaborative control frameworks for CAVs and corresponding applications. Finally, this survey concludes with a discussion of future research directions and the challenges. This survey aims to provide a contextualized and in-depth look at state of the art in vehicle control for AVs and CAVs, identifying critical areas of focus and pointing out the potential areas for further exploration

Dynamic Modeling Accuracy Dependence on Errors in Sensor Measurements, Mass Properties, and Aircraft Geometry

A nonlinear simulation of the NASA Generic Transport Model was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of dynamic models identified from flight data. Measurements from a typical system identification maneuver were systematically and progressively deteriorated and then used to estimate stability and control derivatives within a Monte Carlo analysis. Based on the results, recommendations were provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using other flight conditions, parameter estimation methods, and a full-scale F-16 nonlinear aircraft simulation were compared with these recommendations

Aeronautical Engineering: A special bibliography with indexes, supplement 64, December 1975

This bibliography lists 288 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1975

Ares-I-X Stability and Control Flight Test: Analysis and Plans

The flight test of the Ares I-X vehicle provides a unique opportunity to reduce risk of the design of the Ares I vehicle and test out design, math modeling, and analysis methods. One of the key features of the Ares I design is the significant static aerodynamic instability coupled with the relatively flexible vehicle - potentially resulting in a challenging controls problem to provide adequate flight path performance while also providing adequate structural mode damping and preventing adverse control coupling to the flexible structural modes. Another challenge is to obtain enough data from the single flight to be able to conduct analysis showing the effectiveness of the controls solutions and have data to inform design decisions for Ares I. This paper will outline the modeling approaches and control system design to conduct this flight test, and also the system identification techniques developed to extract key information such as control system performance (gain/phase margins, for example), structural dynamics responses, and aerodynamic model estimations

Dependence of Dynamic Modeling Accuracy on Sensor Measurements, Mass Properties, and Aircraft Geometry

The NASA Generic Transport Model (GTM) nonlinear simulation was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of identified parameters in mathematical models describing the flight dynamics and determined from flight data. Measurements from a typical flight condition and system identification maneuver were systematically and progressively deteriorated by introducing noise, resolution errors, and bias errors. The data were then used to estimate nondimensional stability and control derivatives within a Monte Carlo simulation. Based on these results, recommendations are provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using additional flight conditions and parameter estimation methods, as well as a nonlinear flight simulation of the General Dynamics F-16 aircraft, were compared with these recommendation

Safety Assessment of Road Vehicle in Crosswind Considering Driver Behavior

With expansion of the economy, more and more highway networks extend to coastal areas and mountain valley areas. Vehicles will be exposed to strong crosswinds when driven on these highway roads, especially in hurricane season and in winter in these two different topographic areas. Strong crosswinds threaten the safety of transportation infrastructure and passing vehicles in forms of vehicle accidents that usually result in traffic blockage and driver injury, posing negative effects on economic growth. This dissertation aimed to evaluate the vehicle safety when running through crosswinds in consideration of driver behaviors. Firstly, the aerodynamic characteristics of road vehicles were identified using computational fluid dynamic method. Aerodynamic coefficients of a high-side lorry running in crosswinds using both traditional resultant-wind velocity method and relative-motion approach were compared. In addition, the aerodynamic coefficients of multiple types of vehicles were investigated. The curves of aerodynamic coefficients for different vehicle types against wind yaw angles were obtained. Secondly, an experimental investigation on the vehicle performance and driver behavior was conducted by taking advantage of the LSU’s driving simulator. This study revealed the repeatability of driver behavior and the effect of crosswind speeds on the vehicle performance and drivers’ behavior through a statistical analysis. More scenarios were considered, such as driving in windy-rainy conditions. A regression model of the steering wheel angle turned by drivers was obtained. Finally, safety assessment of vehicles was performed based on an improved wind-vehicle-bridge coupled system and considering driver’s behavior using a series of driver behavior models. For different types of road vehicles, rigid frame vehicle model and flexible frame vehicle model were developed. Accident criteria of lateral side slip, rotational deviation, and rollover were considered. To investigate the influence of driver models, four driver models were considered in different integration methods. Results between cases from different driver models were compared

Mild Hybrid Electric Vehicles: Powertrain Optimization for Energy Consumption, Driveability and Vehicle Dynamics Enhancements

This thesis deals with the modeling, the design and the control of mild hybrid electric vehicles. The main goal is to develop accurate design tools and methodologies for preliminary system and component level analysis. Particular attention is devoted to the configuration in which an electric machine is mounted on the rear axle of a passenger car. The use of such a machine in parallel with the internal combustion engine allows one to exploit different functionalities that are able to reduce the overall fuel consumption of the vehicle. In addition, the indirect coupling between the thermal and the electric machine, realized through the road and not by means of mechanical couplers, together with the position of the latter in the overall vehicle chassis system, enables such an architecture to be efficient both from the energy recovery and the full electric driving point of view. Chapter 1 introduces the problem of fuel consumption and emissions reduction in the overall world context and presents the main hybrid architectures available. Chapter 2 is devoted to the study of the influence of the electric machine position in the powertrain regarding the regenerative braking potentialities concerned. The model considered for the analysis will be described on each of its subcomponents. The braking performance of the vehicle in electric mode is presented considering no losses in the electric powertrain (electric motor, battery, inverter). Chapter 3 is dedicated to the design of an electric machine for a rear axle powertrain. The specifications of such machine are optimized considering both the vehicle and the application under analysis. The design takes into account analytical techniques for the computation of electrical parameters (such as phase and DC currents) and the torque - speed map, as well as numerical ones for its thermal behavior. In Chapter 4 the electrical and thermal characteristics of the designed electric motor are implemented in the model presented in Chapter 2. The overall vehicle model is therefore used both to assess a simple torque split strategy between thermal and electric machine and to perform an optimal sizing of the battery considering all the limitations imposed by the electric powertrain (e. g. maximum currents, maximum temperatures). Chapter 5 makes a step forward and analyzes the different implications that the use of the rear axle electric motor to brake the vehicle has on the vehicle dynamics. Open loop analysis will present a degradation of the vehicle handling comfort caused by the introduction of an oversteering moment to the vehicle. Through the use of a simplified vehicle model, the introduced oversteering yaw moment is evaluated, while a control strategy based on a new stability detector will show how to find a trade off between handling comfort and regenerable energy. At last, Chapter 6 deals with the problem of longitudinal driving comfort. Drivelines and chassis are lightly damped systems and the application of an impulsive torque imposed by the driver can cause the vehicle longitudinal acceleration (directly perceived by the driver) to be oscillating and non smooth. A sensitivity analysis on a conventional powertrain is presented demonstrating which of the different components are more influential in the different modes of vibration, and possible solutions to improve the driveability are proposed. One of these relates to the use of the rear axle electric machine in order to give more responsiveness to the vehicle. Finally, concluding remarks are given in Chapter 7

Flight testing of a remotely piloted vehicle for aircraft parameter estimation purposes

The contribution of this research effort was to show that a reliable RPV could be built, tested, and successfully used for flight testing and parameter estimation purposes, in an academic setting. This was a fundamental step towards the creation of an automated Unmanned Aerial Vehicle (UAV). This research project was divided into four phases. Phase one involved the construction, development, and initial flight of a Remotely Piloted Vehicle (RPV), the West Virginia University (WVU) Boeing 777 (B777) aircraft. This phase included the creation of an onboard instrumentation system to provide aircraft flight data. The objective of the second phase was to estimate the longitudinal and lateral-directional stability and control derivatives from actual flight data for the B777 model. This involved performing and recording flight test maneuvers used for analysis of the longitudinal and lateral-directional estimates. Flight maneuvers included control surface doublets produced by the elevator, aileron, and rudder controls. A parameter estimation program known as pEst, developed at NASA Dryden Flight Research Center (DFRC), was used to compute the off-line estimates of parameters from collected flight data. This estimation software uses the Maximum Likelihood (ML) method with a Newton-Raphson (NR) minimization algorithm. The mathematical model used a traditional static and dynamic derivative buildup. Phase three focused on comparing a linear model obtained from the phase two ML estimates, with linear models obtained from a (i) Batch Least Squares Technique (BLS) and (ii) a technique from the Matlab system identification toolbox. Historically, aircraft parameter estimation has been performed off-line using recorded flight data from specifically designed maneuvers. In recent years, several on-line parameter identification techniques have been evaluated for real-time on-line applications. Along this research line, a novel contribution of this work was to compare the off-line estimation results with results obtained using a recently introduced frequency based on-line estimation method. Specifically, phase four focused on comparing the ML results with a frequency domain based on-line estimation technique. The RPV vehicle and payload was designed and constructed with the combined efforts of WVU researchers, graduate and undergraduate students of the Mechanical and Aerospace Engineering Department, and a private sub-contractor, Craig Aviation