Advances in Intelligent Vehicle Control

Advanced intelligent vehicle control systems have evolved in the last few decades thanks to the use of artificial-intelligence-based techniques, the appearance of new sensors, and the development of technology necessary for their implementation. Therefore, a substantial improvement in vehicle safety, comfort, and performance has been achieved. The appearance of new vehicles with new technologies incorporated in them requires new control strategies that will continue to increase handling, stability, and energy efficiency. In recent years, intelligent vehicle control has been widely investigated from different points of view. Many researchers have studied active safety systems, advanced driver assistance systems, autonomous driver systems, etc., through strategies incorporating aspects of artificial intelligence, making them adapt and learn from situations never explored before. To achieve this, it has been necessary to develop increasingly precise dynamic vehicle models and incorporate new intelligent sensors and sensor fusion techniques to learn the vehicle’s state accurately. However, it is important to observe not only the state of the vehicle where these systems are incorporated but also those of vehicles around it that can influence the vehicle’s behavior. This requires communication between vehicles and developing architectures that enable smart transportation. On the other hand, the incorporation of electric vehicles (EVs) in recent years has enabled a new way of focusing on vehicle control systems, fundamentally due to the incorporation of new systems that must be studied differently. (...)Partial funding for open access charge: Universidad de Málag

An Intelligent Traction Control for Motorcycles

The appearance of anti-lock braking systems (ABS) and traction control systems (TCS) have been some of the most major developments in vehicle safety. These systems have been evolving since their origin, always keeping the same objective, by using increasingly sophisticated algorithms and complex brake and torque control architectures. The aim of this work is to develop and implement a new control model of a traction control system to be installed on a motorcycle, regulating the slip in traction and improving dynamic performance of two-wheeled vehicles. This paper presents a novel traction control algorithm based on the use of Artificial Neural Networks (ANN) and Fuzzy Logic. An ANN is used to estimate the optimal slip of the surface the vehicle is moving on. A fuzzy logic control block, which makes use of the optimal slip provided by the ANN, is developed to control the throttle position. Two control blocks have been tuned. The first control block has been tuned according to the experience of an expert operator. The second one has been optimized using Evolutionary Computation (EC). Simulation shows that the use of EC can improve the fuzzy logic based control algorithm, obtaining better results than those produced with the control tuned only by experience.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A traction Control System based on Co-evolutionary Learning in Spiking Neural Networks (SNN)

A traction control system is designed and trained for different road conditions with co-evolutionary learning based on a genetic algorithm. Common solutions do not consider the variation and oscillation created in the transition between roads defining a control logic which is highly dependent on road accuracy and a speed estimator. To solve this problem, a co-evolutionary learning process is used. This procedure trains the control algorithm, a spiking neural network, on different roads and transitions looking for the worst-case scenario. We have developed a control algorithm with a good dynamic response to constant and changing roads. This control algorithm makes the system stable when the road estimation is delayed or unstable, solving a common flaw produced by sensor noise or computation delays.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Modeling of an Overactuated Vehicle in Simscape Multibody for the Characterization of Suspension and Steering Actuation Systems.

Overactuated systems are increasingly among us. They are used for applications in vehicles, aeronautics and robotics, among others [1, 2]. These systems have a number of advantages, among which we can mention that there are multiple (or infinite) solutions for a given problem. More specifically, in the case of overactuated vehicles, similar states of the system can be achieved in many different ways. These systems are still under development, especially in the field of vehicle dynamics. For example, there are various steer-by-wire algorithms, when the steering of the vehicles is independent, or brake blending strategies. In this work, a part of an overactuated vehicle is designed and validated. This multiphysics model allows to know the plant of the system in much more depth in order to develop control algorithms. More specifically, by modeling the delay of the systems and the nonlinear relationships inherent to multibody systems, much more accurate predictive control can be performed. These results allow a previous validation of the control algorithms in the test platform vehicle being manufactured and developed by the research group, greatly accelerating the control process of each of the overactuated systems of the vehicle.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Low-Cost Surface Classification System Supported by Deep Neural Models

Determining the surface on which a vehicle is moving is vital information for im-proving active safety systems. Performing the surface classification or estimating adherence through tire slippage can lead to late action in possible risk situations. Currently, approaches based on image, sound, or vibration analysis are emerging as a viable alternative, though sometimes complex. This work proposes a methodology based on the use of low-cost accelerometers combined with Deep Learning tech-niques. The performance of the proposed system is evaluated with real tests, where high percentages of accuracy are obtained in the classification task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A study of tensile and bending properties of 3D-printed biocompatible materials used in dental appliances

In the last years, a large number of new biocompatible materials for 3D printers have emerged. Due to their recent appearance and rapid growth, there is little information about their mechanical properties. The design and manufacturing of oral appliances made with 3D printing technologies require knowledge of the mechanical properties of the biocompatible material used to achieve optimal performance for each application. This paper focuses on analyzing the mechanical behaviour of a wide range of biocompatible materials using different additive manufacturing technologies. To this end, tensile and bending tests on different types of recent biocompatible materials used with 3D printers were conducted to evaluate the influence of the material, 3D printing technology, and printing orientation on the fragile/ductile behaviour of the manufactured devices. A test bench was used to perform tensile tests according to ASTM D638 and bending tests according to ISO 178. The specimens were manufactured with nine different materials and five manufacturing technologies. Furthermore, specimens were created with different printing technologies, biocompatible materials, and printing orientations. The maximum allowable stress, rupture stress, flexural modulus, and deformation in each of the tested specimens were recorded. Results suggest that specimens manufactured with Stereolithography (SLA) and milling (polymethyl methacrylate PMMA) achieved high maximum allowable and rupture stress values. It was also observed that Polyjet printing and Selective Laser Sintering (SLS) technologies led to load-displacement curves with low maximum stress and high deformation values. Specimens manufactured with Digital Light Processing (DLP) technology showed intermediate and homogeneous performance. Finally, it was observed that the printing direction significantly influences the mechanical properties of the manufactured specimens in some cases.Universidad de Málag

Control Regenerativo para Motocicleta Eléctrica

Los vehículos cuya transmisión se realiza con motores eléctricos están aumentando dentro de la industria del automóvil y pueden llegar a ser una alternativa fiable a los vehículos con transmisión mediante motores de combustión. Las ventajas fundamentales de este tipo de vehículos es la no emisión de gases contaminantes y ruido y la efectividad de los motores eléctricos con respecto a los de combustión. Entre los problemas que nos encontramos, podemos hablar fundamentalmente de problemas de autonomía, debido a que el sistema de almacenamiento de la energía es poco eficiente, ocupa mucho espacio, es caro y los tiempos necesarios para la recarga son, por el momento, demasiado altos. En este trabajo se desarrollará un sistema de regeneración de energía optimizado. Este sistema obtendrá la máxima potencia de regeneración en los procesos de frenada en el vehículo. Los sistemas actuales regenerativos en motocicletas están diseñados con un factor fijo de regeneración, el cual hace que no deslice la rueda trasera cuando se frena con el freno regenerativo. Este tipo de sistema no aprovecha toda la potencia de regeneración necesaria, ya que da más importancia a la seguridad en la frenada. En el sistema propuesto, se conocerá una información fundamental, la cual es el tipo de carretera por donde circula el vehículo. Con esta información podemos realizar un control basado en lógica difusa, el cual permitirá la obtención de la potencia máxima de frenada sin comprometer el deslizamiento de la rueda trasera.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Detección del tipo de carretera mediante lógica borrosa

Presentación powerpoint de la ponenciaLa aparición de los sistemas seguridad activa tales como los sistemas antibloqueo de frenos (ABS), control de tracción (TCS), control de estabilidad (ESP), direcciones activas (EPS), etc. han sido una evolución fundamental dentro de la seguridad vial. Los sistemas de seguridad activa del coche son aquellos que trabajan para reducir el riesgo de sufrir un accidente. Estos sistemas velan por nuestra seguridad, están en continuo desarrollo e incorporan nuevas funciones continuamente. Para que estos sistemas funcionen adecuadamente necesitan conocer una información fundamental, la cual es el tipo de carretera por donde circulan. Por este motivo se presenta este trabajo. En él se busca conocer el tipo de carretera por donde circula el vehículo mediante técnicas de estimación de las fuerzas de contacto entre la rueda y la calzada y la velocidad del vehículo. El objetivo es realizar esta detección antes de que se produzca una situación de riesgo. Con esto se pretende que los sistemas de control del vehículo puedan actuar de forma más adecuada y rápida ante una situación de peligro, obteniendo con ello una ventaja sustancial frente a los sistemas actuales.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Face Recognition using a Newly Developed Linear Subspace Learning Method

Face recognition is considered a specific physiological biometric in order to identify an individual according to the physical features of the human face. Much research has been conducted in such areas, but still more accurate processes are required for biometric facial recognition. This article presents a novel linear subspace learning method for face recognition which not only can take advantage of principle components analysis (PCA) as a successful feature extraction, but also can apply nearest local centroid mean vector (LMKNCN) as an effective classifier to improve the classification performance. The main goal of this particular scheme is to handle two common existing issues in recognition techniques: named sensitivity to the training sample size and negative effects of outliers. Moreover, to illustrate the performance of proposed developed PCA, we compare it with the latest dimensionality reduction techniques such as traditional PCA and KPCA on publicly available face dataset. Experimental results illustrate that our newly developed method has significantly achieved better performance over the same face database compared with the former KNN-based algorithms

Evaluación de algoritmos de control para sistemas ABS en motocicletas

El sistema de frenado es probablemente el equipamiento de seguridad activa más importante de los vehículos automóviles. La implantación de sistemas de control de frenado y tracción y el esfuerzo científico se están centrando mayoritariamente en los vehículos de cuatro ruedas, siendo escasa la implantación de estos tipos de sistemas en motocicletas, debido a una mayor complicación en el desarrollo y funcionamiento correcto de estos sistemas. Esto repercute en un mayor número de accidentes en los que la motocicleta está involucrada, especialmente cuando el conductor no tiene suficiente experiencia en su conducción. En este trabajo se presentarán los resultados obtenidos en simulaciones realizadas con BikeSim® con diferentes algoritmos de control de ABS para motocicletas. Entre los algoritmos evaluados se encuentran controles basados en PI, en modo deslizante y en lógica borrosa. Además, se incluye una comparativa con un algoritmo basado en un sistema comercial y con una motocicleta sin ABS. Dentro de las tipologías estudiadas se aprecia que los sistemas ABS convencionales reducen la distancia de frenado, sin embargo, no son suficientemente óptimosUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech