Robust automatic steering control for look-down reference systems with front and rear sensors

This paper describes a robust control design for automatic steering of passenger cars. Previous studies [l-3] showed that' reliable automatic driving at highway speed may not be achieved under practical conditions with look-down reference systems which use only one sensor at the front bumper to measure the lateral displacement of the vehicle from the lane reference. An additional lateral displacement. sensor is added here at the tail bumper to solve the automatic steering control problem. The control design is performed stepwise: First, an initial controller is determined using the parameter space approach in an invariance plane. This controller is then refined to accommodate practical constraints and finally optimized using the multi-objective optimization program MOPS. The performance and robustness of the final controller was verified experimentally at California PATH in a series of test runs

Robust Automatic Steering Control for Look-down Reference Systems with Front and Rear Sensors

This paper describes a robust control design for automatic steering of passenger cars. Previous studies [1--3] showed that reliable automatic driving at highway speed may not be achieved under practical conditions with look-down reference systems which use only one sensor at the front bumper to measure the lateral displacement of the vehicle from the lane reference. An additional lateral displacement sensor is added here at the tail bumper to solve the automatic steering control problem. The control design is performed stepwise: First, an initial controller is determined using the parameter space approach in an invariance plane. This controller is then refined to accommodate practical constraints and finally optimized using the multi-objective optimization program MOPS. The performance and robustness of the final controller was verified experimentally at California Path in a series of test runs. Keywords: Automotive, Robust Control, Automatic Steering I. Introduction Automatic ste..

Robust Automatic Steering Control for Look-Down Reference Systems with Front and Rear Sensors

This paper describes a robust control design for automatic steering of passenger cars. Previous studies [l-3] showed that' reliable automatic driving at highway speed may not be achieved under practical conditions with look-down reference systems which use only one sensor at the front bumper to measure the lateral displacement of the vehicle from the lane reference. An additional lateral displacement. sensor is added here at the tail bumper to solve the automatic steering control problem. The control design is performed stepwise: First, an initial controller is determined using the parameter space approach in an invariance plane. This controller is then refined to accommodate practical constraints and finally optimized using the multi-objective optimization program MOPS. The performance and robustness of the final controller was verified experimentally at California PATH in a series of test runs

Driver behavior classification and lateral control for automobile safety systems

Advanced driver assistance systems (ADAS) have been developed to help drivers maintain stability, improve road safety, and avoid potential collision. The data acquisition equipment that can be used to measure the state and parameter information of the vehicle may not be available for a standard passenger car due to economical and technical limitations. This work focuses on developing three technologies (longitudinal tire force estimation, driver behavior classification and lateral control) using low-cost sensors that can be utilized in ADAS. For the longitudinal tire force estimation, a low cost 1Hz positioning global system (GPS) and a steering angle sensor are used as the vehicle data acquisition equipment. A nonlinear extended two-wheel vehicle dynamic model is employed. The sideslip angle and the yaw rate are estimated by discrete Kalman Filter. A time independent piecewise optimization scheme is proposed to provide time-continuous estimates of longitude tire force, which can be transferred to the throttle/brake pedal position. The proposed method can be validated by the estimation results. Driver behavior classification systems can detect unsafe driver behavior and avoid potentially dangerous situations. To realize this strategy, a machine learning classification method, Gaussian Mixture model (GMM), is applied to classify driver behavior. In this application, a low cost 1Hz GPS receiver is considered as the vehicle data acquisition equipment instead of other more costly sensors (such as steering angle sensor, throttle/brake position sensor, and etc.). Since the driving information is limited, the nonlinear extended two-wheel vehicle dynamic model is adopted to reconstruct the driver behavior. Firstly, the sideslip angle and the yaw rate are calculated since they are not available from the GPS measurements. Secondly, a piecewise optimization scheme is proposed to reproduce the steering angle and the longitudinal force. Finally, a GMM classifier is trained to identify abnormal driver behavior. The simulation results demonstrated that the proposed scenario can detect the unsafe driver behavior effectively. The lateral control system developed in this study is a look-down reference system which uses a magnetic sensor at the front bumper to measure the front lateral displacement and a GPS to measure the vehicle\u27s heading orientation. Firstly, the steering angles can be estimated by using the data provided by the front magnetic sensor and GPS. The estimation algorithm is an observer for a new extended single-track model, in which the steering angle and its derivative are viewed as two state variables. Secondly, the road curvature is determined based on the linear relationship with respect to the steering angle. Thirdly, an accurate and real-time estimation of the vehicle\u27s lateral displacements can be accomplished according to a state observer. Finally, the closed loop controller is used as a compensator for automated steering. The proposed estimation and control algorithms are validated by simulation results. The results showed that this lateral steering control system achieved a good and robust performance for vehicles following or tracking a reference path

DESIGN OF A SEMI-ACTIVE STEERING SYSTEM FOR A PASSENGER CAR

This thesis presents research into an improved active steering system technology for a passenger car road vehicle, based on the concept of steer-by-wire (SBW) but possessing additional safety features and advanced control algorithms to enable active steering intervention. An innovative active steering system has been developed as 'Semi-Active Steering' (SAS) in which the rigid steering shaft is replaced with a low stiffness resilient shaft (LSRS). This allows active steer to be performed by producing more or less steer angle to the front steered road wheels relative to the steering wheel input angle. The system could switch to either being 'active' or 'conventional' depending on the running conditions of the vehicle; e.g. during normal driving conditions, the steering system behaves similarly to a power-assisted steering system, but under extreme conditions the control system may intervene in the vehicle driving control. The driver control input at the steering wheel is transmitted to the steered wheels via a controlled steering motor and in the event of motor failure, the LSRS provides a basic steering function. During operation of the SAS, a reaction motor applies counter torque to the steering wheel which simulates the steering 'feel' experienced in a conventional steering system and also applies equal and opposite counter torque to eliminate disturbance force from being felt at the steering wheel during active control operation. The thesis starts with the development of a mathematical model for a cornering road vehicle fitted with hydraulic power-assisted steering, in order to understand the relationships between steering characteristics such as steering feel, steering wheel torque and power boost characteristic. The mathematical model is then used to predict the behaviour of a vehicle fitted with the LSRS to represent the SAS system in the event of system failure. The theoretical minimum range of stiffness values of the flexible shaft to maintain safe driving was predicted. Experiments on a real vehicle fitted with an LSRS steering shaft simulator have been conducted in order to validate the mathematical model. It was found that a vehicle fitted with a suitable range of steering shaft stiffness was stable and safe to be driven. The mathematical model was also used to predict vehicle characteristics under different driving conditions which were impossible to conduct safely as experiments. Novel control algorithms for the SAS system were developed to include two main criteria, viz. power-assistance and active steer. An ideal power boost characteristic curve for a hydraulic power-assisted steering was selected and modified and a control strategy similar to Steer-by-Wire (SBW) was implemented on the SAS system. A full-vehicle computer model of a selected passenger car was generated using ADAMS/car software in order to demonstrate the implementation of the proposed SAS system. The power-assistance characteristics were optimized and parameters were determined by using an iteration technique inside the ADAMS/car software. An example of an open-loop control system was selected to demonstrate how the vehicle could display either under-steer or over-steer depending on the vehicle motion. The simulation results showed that a vehicle fitted with the SAS system could have a much better performance in terms of safety and vehicle control as compared to a conventional vehicle. The characteristics of the SAS system met all the requirements of a robust steering system. It is concluded that the SAS has advantages which could lead to its being safely fitted to passenger cars in the future. Keywords: steer-by-wire, active steering, innovative, power-assisted steering, steering control, flexible shaft, steering intervention, system failure, safety features

Integrated Longitudinal and Lateral Vehicle Guidance via Sliding-Mode-Control

Gegenstand der Arbeit ist der Entwurf eines Fahrerassistenzsystems (FAS) zur automatisierten Längs- und Querführung eines Straßenfahrzeugs. Das FAS soll den Fahrer auf Autobahnen sowie gut ausgebauten Landstraßen unterstützen und entlasten. Dem System können dabei unterschiedliche Architekturen zugrunde liegen. So können zwei parallel betriebene Regelungen die Fahrzeugführung in Längs- und Querrichtung unabhängig voneinander vornehmen. Bei einer kombinierten Längs- und Querführung werden Wechselwirkungen zwischen den vorher separaten Regelungssystemen explizit eingeführt. Für eine integrierte Längs- und Querführung besteht eine implizite Kopplung zwischen den Bewegungsrichtungen. Der Schwerpunkt der Arbeit liegt auf dem Entwurf von Regelungssystemen. Dabei werden zunächst zwei parallel betriebene Regelungen untersucht, die jeweils eine Soll-Beschleunigung in Längs- bzw. Querrichtung erzeugen. Anschließend wird eine integrierte Regelung entworfen, die Soll-Beschleunigungen für beide Bewegungsrichtungen generiert. Als Regelungsprinzip kommen sogenannte Sliding-Mode-Regler zum Einsatz. Dabei handelt es sich um strukturvariable Regler, deren Entwurf im Phasenraum des zu regelnden Systems erfolgt. Für die parallel betriebenen Regler ergeben sich zwei 2D Phasenräume, für den integrierten Ansatz ein 4D Phasenraum. Durch Modifikationen werden die Sliding-Mode-Regler an die Aufgaben der Abstandsregelung, der Fahrstreifenmittenführung sowie der Durchführung eines Überholmanövers bei gleichzeitiger Längsbeschleunigung angepasst. Die Funktionsweise der Regelungen wird anhand zuvor hergeleiteter Modelle der Fahrzeugbewegung untersucht. Die Modellparameter wurden experimentell ermittelt und in Versuchen validiert. Abschließend werden Ergebnisse realer Versuche präsentiert. Hierzu wird ein FAS implementiert, das neben der Regelung geeignete Sensorik zur Erfassung des Fahrzeugumfelds, Aktorik zur Beeinflussung der Fahrzeugbewegung sowie ein Bedienkonzept zur Interaktion des Fahrers mit dem FAS umfasst. Die untersuchten Szenarien beinhalten alltägliche und kritische Situationen. Es wird gezeigt, dass das FAS für die Fahrzeugführung in den beschriebenen Verkehrssituationen geeignet ist und sich eine Parametrierung der Regler anschaulich gestaltet.The subject of this work is the development of a driver assistance system for the automatic longitudinal and lateral guidance of an automobile. The assistance system should support the driver in vehicle guidance on motorways as well as improved highways. The system could be based on different architectures. Thus, two control systems operating in parallel could intervene in the vehicle's longitudinal and lateral guidance independent of each other. In the case of combined longitudinal and lateral control, the interaction between the previously separate control systems is explicitly introduced. An implicit coupling between the two directions of motion exists for the integrated longitudinal and lateral control. This work focuses on the design of control systems. First, two control systems operating in parallel are examined, each of which generates a desired longitudinal and lateral vehicle acceleration respectively. Then an integrated controller for longitudinal and lateral guidance is designed, which generates desired accelerations in both directions of movement. Sliding mode control is applied as the control principle in both approaches. It is a variable structure control system, the design of which takes place in a phase space of the system to be controlled. The two 2D phase spaces for the controls operated in parallel result in a 4D phase space for integrated use. The sliding mode control is modified for tasks of distance control, lane guidance and passing manoeuvres with simultaneous longitudinal acceleration. The manner in which the controls function is examined using previously derived models of vehicle motion. The model parameters were determined experimentally and validated in driving tests. Finally, the results of actual driving tests are presented. For this purpose, a driver assistance system is implemented which includes, in addition to the previously designed controllers, sensors for detecting the vehicle's environment, actuators for influencing vehicle motion as well as an interface between the driver and the assistance system. The examined scenarios include daily and critical driving situations. It is shown that the developed driver assistance system for vehicle guidance is appropriate for the described traffic situations and the parameterization of the control proves to be comprehensible

Reinforcement Learning of Dynamic Collaborative Driving

Dynamic Collaborative Driving is the concept of decentralized multi-vehicle automated driving where vehicles form dynamic local area networks within which information is shared to build a dynamic data representation of the environment to improve road usage and safety. The vision is to have networks of cars spanning multiple lanes forming these dynamic networks so as to optimize traffic flow while maintaining safety as each vehicle travels to its destinations. A basic requirement of any vehicle participating in dynamic collaborative driving is longitudinal and lateral control. Without this capability, higher-level coordination is not possible. This thesis investigates the issue of the control of an automobile in the context of a Dynamic Collaborative Driving system. Each vehicle involved is considered a complex composite nonlinear system. Therefore a complex nonlinear model of the vehicle dynamics is formulated and serves as the control system design platform. Due to the nonlinear nature of the vehicle dynamics, a nonlinear approach to control is used to achieve longitudinal and lateral control of the vehicle. This novel approach combines the use of reinforcement learning: a modern machine learning technique, with adaptive control and preview control techniques. This thesis presents the design of both the longitudinal and lateral control systems which serves as a basis for Dynamic Collaborative Driving. The results of the reinforcement learning phase and the performance of the adaptive control systems for single automobile performance as well as the performance in a multi-vehicle platoon is presented