Path control in limit handling and drifting conditions using State Dependent Riccati Equation technique

Tyres operated at or close to their friction limits show a highly nonlinear motion to force response. This state is called limit handling. The objective of this research is to minimize lateral path tracking error while the tyres operate in limit handling. The State Dependent Riccati Equation technique is employed to develop a feedback-feedforward steering controller. It gives a systematic approach to take into account model nonlinearities such as combined slip tyre characteristics. Furthermore, the controller is implemented in a test vehicle and tested on a low friction skid pad. The controller shows robust path tracking performance even when the rear wheels are operated beyond their friction limits, and large body sideslip prevails

Towards a generic lateral control concept for cooperative automated driving theoretical and experimental evaluation

Lateral vehicle control is an essential part for many automated and cooperative driving applications. Lane keeping and vehicle following are typical modes of such control system. The aim of this paper is to develop a generic lateral controller that can handle these different modes. Based on the available measurements, either path or single point preview information is used in the feedback loop of the controller, while controller parameters and adaptive gains are unaffected. The paper contains theoretical analysis and discusses the results of simulations and vehicle experiments

Path Control in Limits of Vehicle Handling: A Sensitivity Analysis

Sensitivity analysis of a feedback-feedforward steering controller for lateral path tracking whilst the vehicle operates in limit handling is the main objective of this paper. The sensitivity analysis is executed by simulation and the effectiveness of the controller is evaluated in a test vehicle on a low friction skid pad. The results demonstrate that the controller is capable to achieve robust path tracking in limit handling condition for the variety of driving conditions with sufficient stability

Vehicle state estimation using a state dependent Riccati equation

In this paper a Vehicle State Estimator is developed and validated on experimental data from a 2012 Toyota Prius. The estimator is capable of estimating both planar vehicle velocities and the tyre-road friction parameter. Emphasis is placed on the comparison of the commonly used Extended Kalman Filter and a novel application of the State Dependent Riccati Equation technique. The State Dependent Riccati based estimator relies on a factorization compared to linearization in the case of the Extended Kalman Filter. This factorization is non-unique, therefore the construction of this factorization, is also presented. A comparison is for both estimators is presented for experimental data. For estimation of the tyre-road friction parameter, simulations are used, due to absence of a reference value in the experimental set-up

The SWIFT tyre model : overview and applications

The Magic Formula is a very well known tyre model, which is typically applied in vehicle handling simulations. This paper summarises the developments to extend the validity range to higher frequencies (up to 60 Hz), short wavelength excitation and rolling over obstacles. The issues addressed are the dynamics of the tyre belt, contact slip model and enveloping properties. The new tyre model has been validated extensively using experimental results which show that the extended demands can be met. Finally some application examples are given

Extending the Magic Formula and SWIFT tyre models for inflation pressure changes

The Magic Formula and SWIFT tyre models are well-known semi-empirical tyre models for vehicle dynamic simulations. Up to now, the only way to account for inflation pressure changes is to identify all model parameters for each inflation pressure that has to be considered. Since this is a time consuming and consequently expensive activity, research at TNO and Eindhoven University of Technology was started to extend the Magic Formula and SWIFT tyre model so that tyre inflation pressure changes can be accounted for. This paper discusses the influence of inflation pressure changes on the quasi-static force and moment characteristics and on the enveloping properties of tyres. Die Magic Formula und das SWIFT Reifenmodell sind bekannte semi-empirische Reifenmodelle für fahrdynamische Simulationen. Bisher ist die Identifizierung aller Modelparameter für jeden Luftdruck die einzige Möglichkeit um Luftdruckveränderungen zu berücksichtigen. Da das eine zeitraubende und demzufolge teuere Aktivität ist, sind TNO und die TU Eindhoven eine Studie gestartet um die Magic Formula und das SWIFT Reifenmodell zu erweitern damit Luftdruckveränderungen berücksichtigt werden können. Dieser Beitrag geht ein auf den Einfluss von Luftdruckveränderungen auf die quasistatischen Kraftübertragungseigenschaften und auf die quasistatischen Eigenschaften des Reifens auf kurze Fahrbahnunebenheiten

Full vehicle ABS braking using the SWIFT rigid ring tyre model

In recent years, at the Delft University of Technology and TNO-Automotive and in conjunction with an industrial consortium, a pragmatic tyre model has been developed going by the name SWIFT, which is geared to the analysis of tyre oscillations and its effects on vehicle behaviour. The SWIFT tyre model has been designed to cover in-plane, out-of-plane and combined higher order dynamic tyre performance. It can be regarded as an extension of the Magic Formula pragmatic tyre model, up to a range of at least about 70 Hz. This paper describes the application of the SWIFT tyre model to full vehicle ABS braking. First, the model is used to derive the single tyre response to road undulations and brake torque step input, both being very much of relevance to ABS braking. This includes a survey of the sensitivity of the dynamic tyre parameters regarding the first, rigid belt, eigenfrequencies and the relative damping. Next, the response of a quarter vehicle to similar input is discussed with specific emphasis on the added value of the dynamic characteristics of the SWIFT model in comparison to steady state and transient tyre models. Finally, full vehicle ABS controlled braking on an even road is considered for various road friction values and vehicle speed

AUTOPILOT Deliverable 1.2: Final specification of IoT-enabled Autonomous Driving use cases

This document presents the final specification of use cases aimed to assess the potential of Internet of Things for enhancement and enabling of Automated Driving in AUTOPILOT project

IoT solutions for large open-air events

This chapter presents the main results of the MONICA project, one of the five large-scale pilot projects funded by the European Commission. MONICA focuses on the adoption of wearable IoT solutions for the management of safety and security in large open-air events as well as on the reduction of noise level for neighbours. The project addresses several challenges in eleven pilots of six major European cities using a large number of IoT wearables and sensors. The chapter first introduces all MONICA challenges in the context of large open-air events and then presents the corresponding adopted technical solutions, the defined IoT architecture and the perspective in integrating a wide range of heterogeneous sensors. On one side, the focus is on the solutions that have been adopted to improve the crowd management, crowd safety and emergency responses by using wearables for both visitors and the security staff at the events, including also the adoption of video processing and data fusion algorithms to estimate the number of visitors and its distribution in the event area and to detect suspicious activity patterns. On the other hand, it describes how innovative Sound Level Meters (SLMs) can be deployed to monitor the sound propagation within the event area while reducing the noise impact on the neighbourhood

IoT Technologies for Connected and Automated Driving Applications

The applications of the Internet of Things (IoT) technologies connect mul-tiple devices directly and through the Internet. Autonomous vehicles utiliseconnectivity when updating their algorithms based on user data, interact withthe infrastructure to get environmental information, communicate with othervehicles. They exchange information with pedestrians using mobile devicesand wearables and provide information about the traffic attributes and datacollected by the vehicle sensors. The connected and automated vehicles(CAV) require a significant quantity of collecting and processing data andthrough IoT applications and services the autonomous vehicles share information about the road, the present path, traffic, and how to navigate arounddifferent obstacles. This information can be shared between IoT connectedvehicles and uploaded wirelessly to the cloud or/and edge system to be anal-ysed and operated improving the levels of automation and the autonomousdriving (AD) functions of each vehicle. This chapter gives an overview ofthe integration of IoT devices contributing to automated/autonomous driving, and the IoT infrastructure deployed and seamlessly integrated into theAUTOPILOT project use cases and pilot demonstrators, including the IoTplatforms integration