Design of an Estimator Using the Artificial Neural Network Technique to Characterise the Braking of a Motor Vehicle

Automatic systems are increasingly being applied in the automotive industry to improve driv-ing safety and passenger comfort, reduce traffic, and increase energy efficiency. The objective of this work is focused on improving the automatic brake assistance systems of motor vehicles trying to imitate human behaviour, but correcting possible human errors such as distractions, lack of visibility or time reaction. The proposed system can optimise the intensity of the braking according to the available distance to carry out the manoeuvre and the vehicle speed to be as less aggressive as possible, thus giving priority to the comfort of the driver. A series of tests are car-ried out in this work with a vehicle instrumented with sensors that provide real-time infor-mation about the braking system. The data obtained experimentally during the dynamic tests are used to design an estimator using the Artificial Neural Network (ANN) technique. This in-formation makes it possible to characterise all braking situations based on the pressure of the brake circuit, the type of manoeuvre and the test speed. Thanks to this ANN it is possible to es-timate the requirements of the braking system in real driving situations and carry out the ma-noeuvres automatically. Experiments and simulations verified the proposed method for the es-timation of braking pressure in real deceleration scenarios

Practical Case Application for Stress Model Validation and Enhancement by Means of Metrological Tools

Models consider ideal and simplified situations that will never be met in the real case. The process of comparing model predictions and experimental observation is in the basis of scientific research. This comparison is however complicated because of the uncertainties of the model input data and the difficulty to control the accuracy of the tests and to obtain a significant statistical sampling. Moreover, there isn't yet a consensus on a validation parameter. This paper presents a three-step validation procedure that allows quantifying the application limits of a two-dimensional stress model in a three-dimensional situation. A global uncertainty model is calculated comprising the uncertainty of the model and also the uncertainty coming from the experimental results. The EN number, a statistical magnitude for interlaboratory comparisons, is used to analyse the compatibility between the experimental and theoretical results. Finally, a bootstrapping method is proposed to calculate the coverage interval of the sampling and determine if new experiments should be carried out. Numerical results of this new validation procedure are provided for the case under study. It is also demonstrated that the computed uncertainty budget can be a useful tool to enhance the two-dimensional model by enlarging its uncertainty limits

Surface Electromyography Study Using a Low-Cost System: Are There Neck Muscles Differences When the Passenger Is Warned during an Emergency Braking Inside an Autonomous Vehicle?

Deaths and serious injuries caused by traffic accidents is a concerning public health problem. However, the problem can be mitigated by the Autonomous Emergency Braking (AEB) system, which can avoid the impact. The market penetration of AEB is exponentially growing, and non-impact situations are expected to become more frequent. Thus, new injury patterns must be analysed, and the neck is particularly sensitive to sudden acceleration changes. Abrupt braking would be enough to be a potential risk for cervical spine injury. There is controversy about whether or not there are differences in cervical behaviour depending on whether passengers are relaxed or contract their muscles before the imminent accident. In the present manuscript, 18 volunteers were subjected to two different levels of awareness during an emergency braking test. Cervical muscles (sternocleidomastoid and trapezius) were analysed by the sEMG signal captured by means of a low-cost system. The differences observed in the muscle response according to gender and age were notable when passengers are warned. Gender differences were more significant in the post-braking phase. When passengers were relaxed, subjects older than 35 registered higher sEMG values. Meanwhile, when passengers contract their muscles, subjects who were younger than or equal to 35 years old experienced an increment in the values of the sEMG signals

Study of the Emergency Braking Test with an Autonomous Bus and the sEMG Neck Response by Means of a Low-Cost System

This article belongs to the Special Issue Development of Innovative Sensor Platforms for Field AnalysisNowadays, due to the advances and the increasing implementation of the autonomous braking systems in vehicles, the non-collision accident is expected to become more common than a crash when a sudden stop happens. The most common injury in this kind of accident is whiplash or cervical injury since the neck has high sensitivity to sharp deceleration. To date, biomechanical research has usually been developed inside laboratories and does not entirely represent real conditions (e.g., restraint systems or surroundings of the experiment). With the aim of knowing the possible neck effects and consequences of an automatic emergency braking inside an autonomous bus, a surface electromyography (sEMG) system built by low-cost elements and developed by us, in tandem with other devices, such as accelerometers or cameras, were used. Moreover, thanks to the collaboration of 18 participants, it was possible to study the non-collision effects in two different scenarios (braking test in which the passenger is seated and looking ahead while talking with somebody in front of him (BT1) and, a second braking test where the passenger used a smartphone (BT2) and nobody is seated in front of him talking to him). The aim was to assess the sEMG neck response in the most common situations when somebody uses some kind of transport in order to conclude which environments are riskier regarding a possible cervical injury

Methodology for bus structure torsion stiffness and natural vibration frequency prediction based on a dimensional analysis approach

Engineering bus design requires testing of bus structures prototypes in order to guarantee a certain level of strength and an appropriate static and dynamic behavior of the bus superstructure when exposed to road loads. However, experimental testing of real bus structures is very expensive as it requires expensive resources and space. If testing is done on a scale bus model the previous required expenses are considerably reduced. Therefore, a novel methodology based on dimensional analysis applied to bus structure prediction to evaluate the bus structure static and dynamic performance is proposed. The static performance is evaluated attending to torsion stiffness and the dynamic in terms of the natural vibration frequencies and rollover threshold. A scale bus has been manufactured and dimensionless parameters have been defined in order to project the results obtained in the scale bus model to a larger model. Validation of the proposed methodology has been carried out under experimental and finite element analysis.The authors gratefully acknowledge the funds provided by the Regional Government of Madrid through the project CCG10-UC3M/DPI-4614Publicad

Sideslip angle estimator based on ANFIS for vehicle handling and stability

Most of the 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 literature. The modeling of sideslip angle is complex due to the non-linear dynamics of the vehicle. This work proposes a new methodology based on ANFIS to estimate the vehicle sideslip angle. The estimator has been validated by comparing the proposed ANFIS prediction model with the values provided by CARSIM model, which is an 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-based sideslip angle estimator.Acknowledge use of the services and facilities of the Research Institute of Vehicle Safety (ISVA) at Carlos III University and the the funds provided by the Regional Government of Madrid through the research project CCG10-UC3M/DPI-4614

Design of an estimator based on artificial neural networks to characterize the braking of a vehicle

Hoy en día, los vehículos inteligentes están equipados con interfaces de usuario muy avanzadas que pueden reaccionar ante las decisiones y necesidades del conductor. De esta manera mejora la dinámica vehicular según la situación de conducción evitando posibles colisiones fortuitas. Esta tecnología permite tomar decisiones sobre la conducción con un nivel de resolución superior al humano a la hora de, por ejemplo, realizar una frenada de emergencia ante un imprevisto. Con este trabajo se pretende que, en un futuro, se pueda gobernar el sistema de frenado de manera automática y que el vehículo pueda reproducir los hábitos y las formas de actuación de los conductores durante la maniobra de frenada de un vehículo, pero corrigiendo los posibles fallos humanos ligados a distracciones, falta de visibilidad o tiempos de reacción. Un sistema de frenado inteligente ha de ser capaz de obtener información de los diferentes sensores embarcados en el vehículo, procesar los datos obtenidos a través de los mismos y transformarlos en información útil para el control activo del automóvil. Con el vehículo instrumentado con los sensores capaces de proporcionar en tiempo real información sobre el sistema de frenado se llevan a cabo una serie de ensayos. Los datos obtenidos experimentalmente durante la realización de los ensayos se utilizan para el diseño de un estimador mediante la técnica de redes neuronales artificiales. Se estimarán las variables medidas por los sensores con el fin de caracterizar una frenada.Today, smart vehicles are equipped with highly advanced user interfaces that can react to the driver’s decisions and needs. In this way, it improves vehicle dynamics according to the driving situation and avoiding possible accidental collisions. This technology makes it possible to make decisions about driving with a level of resolution higher than human, for example, carrying out an emergency braking in the event of an unforeseen event. With this work it is intended that, in the future, the braking system can be governed automatically and that the vehicle can reproduce drivers’ habits and forms of action during the braking maneuver of a vehicle, but correcting the possible human failures linked to distractions, lack of visibility and reaction times. An intelligent braking system must be able to obtain information from the different sensors on board the vehicle, process the data obtained through them and transform them into useful information for the active control of the car. With the vehicle instrumented with sensors capable of providing real-time information about the braking system, a series of tests are carried out. The data obtained experimentally during the tests are used to design an estimator using the artificial neural network technique. The variables measured by the sensors will be estimated in order to characterize a braking

Development and characterization of a compact device for measuring the braking torque of a vehicle

In This Article, A New Force Transducer Is Designed, Developed And Built For The Measurement Of Braking Forces In The Wheel Rim Of A Motor Vehicle. The Parameters Of The Transducer Design Are Justified Using Numerical Simulation. In Order To Install It In The Vehicle In A Simple And Interference-Free Way, The Metal Base Of The Caliper Rod Is Used. It Is Manufactured And Installed In A Vehicle In Order To Obtain The Signals Of The Wheel Braking Torque, In Real Time, And At Different Speeds Of Circulation, Carrying Out Several Tests On The Track. Subsequently, Data Are Obtained From Calculations Of The Disc Brake System Itself. The Latter Provides Instantaneous Adherence Values Between The Brake Pad And The Disc