The Impact of Virtual Environments for Future Electric Powered-Mobility Development Using Human-in-the-Loop: Part B - Virtual Testing and Physical Validation

Electric vehicles are increasing in popularity worldwide, and there have been numerous advances in technology to increase the energy efficiency of the vehicle and reduce the range anxiety for the user. For example, the latest electric vehicle (Tesla model S, equipped by 100kWh battery) available in the market in 2019 is able to drive around 375 miles. However, human behavior such as driving strategy is an important issue that impacts on energy optimization and ultimately vehicle range. Human behavior is rather complex and is difficult to replicate with computer algorithms. Therefore, to fully assess the impact of a particular technology, the interactions between humans, vehicle, and the environment need to be examined simultaneously, through a Human-in-the-Loop approach. In this chapter, the results of investigating a human-in-the-loop test platform, which incorporate human-driving behavior and the vehicle characteristics, are presented. In addition, this chapter analyzes a driving strategy, using a Human-in-the-Loop approach, applied to optimizing the energy usage for an electric vehicle competition

Developing Automotive Products Using the EAST-ADL2, an AUTOSAR Compliant Architecture Description Language

International audienceCurrent development trends in automotive software feature increasing standardization of the embedded software structure. But it still remains the critical issue of the overall engineering information management to control the system definition and manage its complexity. System modeling based onan Architecture Description Language (ADL) is a way to keep these assets within one information structure. The original EAST-ADL was developed in the EAST-EEA project (www.east-eea.org) and basic concepts were reused in the AUTOSAR standardization initiative. The original EAST-ADL is currently refined in the ATESST project (www.atesst.org) to EAST-ADL2. This paper presents the results of the language extension provided by the EAST-ADL2 domain model and focuses on its possible extension of the AUTOSAR standard to support decomposition of E/E automotive systems

LMI-based H∞ controller of vehicle roll stability control systems with input and output delays

This article belongs to the Section Physical Sensors.Many of the current research works are focused on the development of different control systems for commercial vehicles in order to reduce the incidence of risky driving situations, while also improving stability and comfort. Some works are focused on developing low-cost embedded systems with enough accuracy, reliability, and processing time. Previous research works have analyzed the integration of low-cost sensors in vehicles. These works demonstrated the feasibility of using these systems, although they indicate that this type of low-cost kit could present relevant delays and noise that must be compensated to improve the performance of the device. For this purpose, it is necessary design controllers for systems with input and output delays. The novelty of this work is the development of an LMI-Based H∞ output-feedback controller that takes into account the effect of delays in the network, both on the sensor side and the actuator side, on RSC (Roll Stability Control) systems. The controller is based on an active suspension with input and output delays, where the anti-roll moment is used as a control input and the roll rate as measured data, both with delays. This controller was compared with a controller system with a no-delay consideration that was experiencing similar delays. The comparison was made through simulation tests with a validated vehicle on the TruckSim® software.This work was supported by the FEDER/Ministry of Science and Innovation-Agencia Estatal de Investigacion (AEI) of the Government of Spain through the project [RTI2018-095143-B-C21]

Optical wireless for intravehicle communications : incorporating passenger presence scenarios

Through the implementation of a simple linearly scalable 1-W infrared (IR) transmitter, which is centrally located on the ceiling of a sports utility vehicle (SUV), and for 15 passenger configurations, an analysis into the received power, power deviation, minimum bandwidth, and maximum root-mean-square (RMS) delay spread is provided for the regions of the vehicle most likely to benefit from the deployment of intravehicle optical wireless (OW) communication systems. Several specific regions, including the areas around a passenger's legs, arms, necks, and shoulders, are shown to have beneficial channel characteristics for the use of personal electronics equipment such as laptops, tablet PCs, or wireless headphones. Similarly, a region around the headrest of the front seat is shown to have potential for the deployment of in-car entertainment solutions independent of the passenger configuration. This analysis, which is the first to introduce the concept of channel variation from multiple passenger configurations, aims to show that OW is a potential candidate for future intravehicular communication systems

VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles

Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from sensors. For this goal, it is necessary to mount on vehicles not only low-cost sensors, but also low-cost embedded systems, which allow acquiring data from sensors and executing the developed algorithms to estimate and to control with novel higher speed computing. All these devices have to be integrated in an adequate architecture with enough performance in terms of accuracy, reliability and processing time. In this article, an architecture to carry out the estimation and control of vehicle dynamics has been developed. This architecture was designed considering the basic principles of IoT and integrates low-cost sensors and embedded hardware for orchestrating the experiments. A comparison of two different low-cost systems in terms of accuracy, acquisition time and reliability has been done. Both devices have been compared with the VBOX device from Racelogic, which has been used as the ground truth. The comparison has been made from tests carried out in a real vehicle. The lateral acceleration and roll rate have been analyzed in order to quantify the error of these devices.This work might not have been possible had it not been for the funds provided by the Spanish Government through the projects TRA2013-48030-C2-1-R and TRA2008-05373/AUT

A Simulation Tool Chain for Investigating Future V2X-based Automotive E/E Architectures

Due to the evermore rising number of functions, current E/E architectures are more and more a vulnerable source for faults and a barrier to innovation. This situation is aggravated by the integration of new technologies like Vehicle-to-X Communication (V2XC) which form the basis for a large number of future services and applications. At the same time, this “opening” of the E/E architecture to the outside world increases potential for non-deterministic disturbances. In order to overcome the limitations of current E/E architectures, application of new design principles and methodologies is necessary. Platform-based design (PBD) is a promising solution for the development of safety-critical functions, to increase reliability and to reduce development cost. Within this context, we propose a novel extensible tool chain that targets the facilitation of exploration, validation and verification of future V2X-based automotive E/E architectures. The tool chain supports composition of heterogeneous domain-specific models by integrating a heterogeneous modeling tool with a simulation middleware and serves as starting point for the investigation of PBD concepts in the V2X context. We believe that the tool chain can support modeling and validation of future V2X-based E/E architectures. In the final paper, we will evaluate the proposed approach by means of a case study regarding validation capabilities as well as execution performance

Development of a Test-Bench for Evaluating the Embedded Implementation of the Improved Elephant Herding Optimization Algorithm Applied to Energy-Based Acoustic Localization

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Real-Time Vehicle Roll Angle Estimation Based on Neural Networks in IoT Low-Cost Devices

The high rate of vehicle-crash victims has a fatal economic and social impact in today's societies. In particular, road crashes where heavy vehicles are involved cause more severe damage because they are prone to rollover. For this reason, many researches are focused on developing RSC Roll Stability Control (RSC) systems. Concerning the design of RSC systems with an adequate performance, it is mandatory to know the dynamics of the vehicle. The main problem arises from the lack of ability to directly capture several required dynamic vehicle variables, such as roll angle, from low-cost sensors. Previous studies demonstrate that low-cost sensors can provide data in real-time with the required precision and reliability. Even more, other research works indicate that neural networks are efficient mechanisms to estimate roll angle. Nevertheless, it is necessary to assess that the fusion of data coming from low-cost devices and estimations provided by neural networks can fulfill hard real-time processing constraints, achieving high level of accuracy during circulation of a vehicle in real situations. In order to address this issue, this study has two main goals: (1) Design and develop an IoT based architecture, integrating ANN in low cost kits with different hardware architectures in order to estimate under real-time constraints the vehicle roll angle. This architecture is able to work under high dynamic conditions, by following specific best practices and considerations during its design; (2) assess that the IoT architecture deployed in low-cost experimental kits achieve the hard real-time performance constraints estimating the roll angle with the required calculation accuracy. To fulfil these objectives, an experimental environment was set up, composed of a van with two set of low-cost kits, one including a Raspberry Pi 3 Model Band the other having an Intel Edison System on Chip linked to a SparkFun 9 Degrees of Freedom module.This research was funded by Spanish Government through the projects TRA2013-48030-C2-1-R and TRA2008-05373/AUT