Autonomous path following and emergency braking control for intelligent vehicles using low cost devices

Proceeding of: 15th International Symposium on Advanced Vehicle Control (AVEC '22), September 12-15, 2022, Kanagawa, JapanThe novelty of this paper is an Event-Triggered LPV Output-Feedback H∞ controller that generates a steering control signal to follow the road, an acoustic sensor based AEB-P system which avoids vehicle collision with pedestrians and a speed controller based on the curvature of the path. The validation of the proposed system is done through simulation tests with CarSim®This work was supported by the FEDER/Ministry of Science and Innovation - Agencia Estatal de Investigación (AEI) of the Government of Spain through the project [RTI2018-095143-B-C21]

A novel frequency dependent model based on trigonometric functions for a magnetorheological damper

In this paper, a novel frequency dependent MR damper model based on trigonometric functions is proposed. The model presents the following advantages in comparison with other previously proposed models: (1) it is based on algebraic functions instead of differential equations, so that it does not present convergence problems when noisy inputs from experimental measurements are used; (2) the number of parameters is reasonable, so that it makes the model computationally efficient in the context of parameter identification and (3) the model has to take into account the variation of the parameters as a function, not only of the applied current but also of the frequency of excitation. Experimental results confirm that the proposed frequency dependent MR damper model improves the accuracy of the model in force simulation.Funds provided by the Spanish Government through the CICYT Projects TRA2008-05373/AUT and TRA2011-28548-C02-0

A Novel Inverse Dynamic Model for a Magnetorheological Damper based on Network Inversion

Semi-active suspensions based on magnetorheological (MR) dampers are receiving significant attention specially for control of vibration isolation systems. The nonlinear hysteretic behaviour of MR dampers can cause serious problems in controlled systems such as instability and loss of robustness. Most of the developed controllers determine the desired damping forces which should be produced by the MR damper. Nevertheless, the MR damper behaviour can only be controlled in terms of the applied current (or voltage). In addition to this, it is necessary to develop an adequate inverse dynamic model in order to calculate the command current (or voltage) for the MR damper to generate the desired forces as close as possible to the optimal ones. Due to MR dampers are highly nonlinear devices, the inverse dynamics model is difficult to obtain. In this paper, a novel inverse MR damper model based on a network inversion to estimate the necessary current (or voltage) such as the desired force is exerted by the MR damper is presented. The proposed inverse model is validated carrying out experimental tests. In addition, a comparison of simulated tests with other damper controllers is also presented. Results show the effectiveness of the network inversion for inverse modeling of an MR damper, so that the proposed inverse model can act as a damper controller to generate the command current (or voltage) to track the desired damping force.This work was supported by the funds provided by the Spanish Government through the CICYT projects TRA2008-05373/AUT and TRA2011-28548-C02-01.Publicad

Sensor fusion based on a Dual Kalman Filter for estimation of road irregularities and vehicle mass under static and dynamic conditions

Mass is an important parameter in vehicle dynamics because it affects not only safety but also comfort. The mass influences the three movements corresponding to vehicle dynamics. Therefore, having an accurate value of mass is essential for having a suitable model which will lead to proper controller and observer operation. Additionally, unlike other vehicle parameters, the mass can vary during a trip due to loading and unloading items and passengers onto the vehicle, greatly influencing its dynamics. This is critical in heavy vehicles where the mass can vary by around 400%. Therefore, the mass must be updated on-line. The novelty of this paper is the construction of a state-parameter observer which allows the mass under static and dynamic driving conditions to be estimated using measurements from sensors that can be mounted easily on vehicles. In this study, a vertical complete model is considered based on the dual Kalman filter for mass and road irregularities estimation using the data obtained from suspension deflection sensors and a vertical accelerometer. Both simulation and experimental results are carried out to prove the effectiveness of the proposed algorithm.This work was supported by Projects TRA2008-05373/AUT and TRA2013-48030-C2-1-R from the Spanish Ministry of Economy and Competitiveness

A robust observer based on energy-to-peak filtering in combination withneural networks for parameter varying systems and its application to vehicleroll angle estimation

This paper presents a robust observer based on energy-to-peak filtering in combination with a neural network for vehicle roll angle estimation. Energy-to-peak filtering estimates the minimised error for any bounded energydisturbance. The neural network acts as a 'pseudo-sensor' to estimate a vehicle 'pseudo-roll angle', which is used as the input for the energy-to-peak-based observer. The advantages of the proposed observer are as follows. 1) Itdoes not require GPS information to be utilised in various environments. 2) It uses information obtained from sensors that are installed in current vehicles, such as accelerometers and rate sensors. 3) It reduces computationtime by avoiding the calculation of observer gain at each time sample and utilising a simplified vehicle model. 4) It considers the uncertainties in parameters of the vehicle model. 5) It reduces the effect of disturbances. Bothsimulation and experimental results demonstrate the effectiveness of the proposed observer.This work is supported by the Spanish Government through the Project TRA2013-48030-C2-1-R, which is gratefully acknowledged

Vehicle sideslip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm

Most existing ESC (Electronic Stability Control) systems rely on the measurement of both yaw rate and sideslip angle. However, one of the main issues is that the sideslip angle cannot be measured directly because the sensors are too expensive. For this reason, sideslip angle estimation has been widely discussed in the relevant literature. The modeling of sideslip angle is complex due to the non-linear dynamics of the vehicle. In this paper, we propose a novel observer based on ANFIS, combined with Kalman Filters in order to estimate the sideslip angle, which in turn is used to control the vehicle dynamics and improve its behavior. For this reason, low-cost sensor measurements which are integrated into the actual vehicle and executed in real time have to be used. The ANFIS system estimates a "pseudo-sideslip angle" through parameters which are easily measured, using sensors equipped in actual vehicles (inertial sensors and steering wheel sensors); this value is introduced in UKF in order to filter noise and to minimize the variance of the estimation mean square error. The estimator has been validated by comparing the observed proposal with the values provided by the CARSIM model, which is a piece of experimentally validated software. The advantage of this estimation is the modeling of the non-linear dynamics of the vehicle, by means of signals which are directly measured from vehicle sensors. The results show the effectiveness of the proposed ANFIS+UKF-based sideslip angle estimator

Study of van roadworthiness considering their maintenance and periodic inspection. The Spanish case

In Europe, traffic road safety has clearly improved due to many factors. One of them is the improvement of the roadworthiness. However, accidents of vans and light goods vehicles (LGV) have not followed the decreasing tendency of other vehicles. Several studies suggest that vehicle defects are relevant to the cause of accidents. It would be ideal if vehicle owners continuously kept their vehicles in compliance with the roadworthiness standards. Another important aspect to operate with roadworthy vans is the maintenance programs. It is probable that many van owners do not adequately maintain their vehicles or the maintenance programs are not sufficient with the periodic motor vehicle inspections (PMVI) intervals or with the items inspected. This paper analyses the maintenance schedules and PMVI of vans in order to assess the influence of these parameters in their higher accident rate. The conclusions provided can enable public administrations to modify enforcement laws, regarding time control of driving and PMVI.Proyecto financiado por el Ministerio de Fomento en el marco del Plan I+D+i 2008/2011: Desarrollo y aplicación de una metodología integrada para el estudio de los accidentes de tráfico con implicación de furgonetas (P24/08)”. FURGOSEG

Simultaneous Estimation of Vehicle Sideslip and Roll Angles Using an Integral-Based Event-Triggered Hinfinity Observer Considering Intravehicle Communications

In recent years, several technological advances have been incorporated into vehicles to ensure their safety and ride comfort. Most of these driver-assistance technologies aim to prevent skidding, whereas less attention has been paid to the avoidance of other dangerous situations such as a rollover. Since knowledge of slip and roll angles is critical to the control and safety of vehicle handling, their estimation remains of great interest when addressing emerging constraints in modern technologies involving networked communications and distributed computing. This paper presents an integral-based event-triggered H ¿ observer to simultaneously estimate the sideslip and roll angles, considering intravehicle communications with a networked-induced delay. As the longitudinal velocity and tire cornering stiffness of a vehicle can vary significantly during driving and have a strong influence on vehicle lateral stability, these time-varying parameter uncertainties are considered in the design of the observer. The simulation and experimental results demonstrate the effectiveness of the proposed observer.This work was supported by the Agencia Estatal de Investigacion (AEI) of the Ministry of Science and Innovation of the Government of Spain through the project RTI2018-095143-B-C2

Sistema de control para robots móviles autónomos basado en habilidades reactivas

Un robot autónomo móvil debe ser capaz de adaptarse de manera flexible a cambios que se produzcan en el entorno sin la necesidad de decirle qué hacer en cada momento. La aptitud de un robot de decidir cómo actuar ante una determinada situación y de reaccionar adecuadamente ante eventos para ejecutar sus tareas de manera segura va a depender de cómo estén distribuidas las capacidades de deliberación y reacción en él. La arquitectura de control híbrida AD se basa en la forma en la que se organizan los procesos mentales humanos. Consta de dos niveles: uno Deliberativo que está relacionado con la capacidad de razonar, y otro Automático que está relacionado con las capacidades de ejecutar acciones de manera automática. Uno de los objetivos de esta tesis consiste en el desarrollo del nivel Au­tomático de la arquitectura AD. Este nivel permite al robot disponer de la necesaria reactividad para responder rápidamente a cambios que se produzcan en el entorno. Está formado por habilidades automáticas que incluyen las capacidades de percepción y acción del robot y por acciones reflejas que permiten al robot responder de manera prioritaria ante determinados estímulos. En esta tesis se ha definido una estructura genérica para habilidades que facilita su programación, integración y modificación en la arquitectura de control de manera que no afecte al resto de los componentes que constituyen dicha arquitectura. Las habilidades pueden ejecutarse en paralelo, son acti­vadas por el nivel Deliberativo cuando se necesitan para llevar a cabo una determinada tarea y generan sus propios eventos notificándoselo a aquellas habilidades que se hayan registrado en ella para recibirlos. También se propone tres diferentes métodos de generación de habilidades complejas a partir de habilidades ya existentes denominados secuenciación, adición de salidas y flujo de datos. Estos tres métodos no son excluyentes sino que pueden darse en una misma habilidad. El nivel Deliberativo tiene que conocer cuales son las habilidades au­tomáticas de las que dispone para ejecutar una tarea determinada. Se presenta una base de datos que contiene información acerca de las habilidades automáticas que le puede servir al nivel Deliberativo para razonar o tomar decisiones. Por último, se propone un algoritmo de aprendizaje por refuerzo basado en redes neuronales que permite a un robot móvil aprender habilidades sensorimotoras automáticas sencillas. De esta manera, el robot es capaz de aprender a adaptarse y a reaccionar para mejorar su actuación. El algoritmo de aprendizaje propuesto trabaja con espacios de entrada y salida continuos y señal de refuerzo continua.An autonomous mobile robot must be able to flexibly adapt its behaviors without explicitly being told what to do in each situation. Robot 's decision capacity to react to events in arder to carry out its tasks safely depends on how its deliberation and reaction capacities are organized on it. The hybrid control architecture called AD is based on how mental processes are performed in humans. It has two levels: one is the Deliberative level which is related to reasoning capacity and the another is the Automatic level which is related to execution of automatic actions. One of the objectives of this PhD Thesis is to develop the Automatic level of the architecture AD. This level allows the robot to react to changes took place in the environment. It is formed by automatic skills which include the robot's perception and action capacities, and by reflex actions which allow the robot to respond with priority to a specific stimulus. A generic structure for skills is defined which makes its programming, modification and integration easier so it does not affect the other architec­ture's components. Skills can execute parallel, are activated by the Deliber­ative level and generate their own events notifying them to skills which have registered at it in order to receive the events. Three different methods are also proposed for generating complex skills from simple ones called sequencing, output addition and data fiow. These methods are not exclusive but they can be in the same skill. The Deliberative level has to know what are the available automatic skills in order to perform a task. A data base is presented which contains infor­mation about skills useful for the Deliberative level for reasoning or taking decisions. Finally, a reinforcement learning algorithm is proposed based on neural networks which allows a mobile robot to learn simple automatic sensorimotor skills. In this case, the robot is capable of learning to adapt and react in order to improve its performance. The proposed learning algorithm works with continuous inputs and outputs and continuous reinforcement signal.Doctor por la Universidad Carlos III de Madrid. Programa en Tecnologías IndustrialesPresidente: Carlos Balaguer Bernaldo de Quirós.- Secretario: Luis Enrique Moreno Lorente.- Vocales: Jesús Manuel de la Cruz García, Fernando Morilla García y Antonio Barriento

A LQR-based controller with estimation of road bank for improving vehicle lateral and rollover stability via active suspension

In this article, a Linear Quadratic Regulator (LQR) lateral stability and rollover controller has been developed including as the main novelty taking into account the road bank angle and using exclusively active suspension for both lateral stability and rollover control. The main problem regarding the road bank is that it cannot be measured by means of on-board sensors. The solution proposed in this article is performing an estimation of this variable using a Kalman filter. In this way, it is possible to distinguish between the road disturbance component and the vehicle's roll angle. The controller's effectiveness has been tested by means of simulations carried out in TruckSim, using an experimentally-validated vehicle model. Lateral load transfer, roll angle, yaw rate and sideslip angle have been analyzed in order to quantify the improvements achieved on the behavior of the vehicle. For that purpose, these variables have been compared with the results obtained from both a vehicle that uses passive suspension and a vehicle using a fuzzy logic controller.This work might not have been possible without the funds provided by the Spanish Government through the projects TRA2013-48030-C2-1-R and TRA2008-05373/AUT