26,149 research outputs found
Simulation of Mixed Critical In-vehicular Networks
Future automotive applications ranging from advanced driver assistance to
autonomous driving will largely increase demands on in-vehicular networks. Data
flows of high bandwidth or low latency requirements, but in particular many
additional communication relations will introduce a new level of complexity to
the in-car communication system. It is expected that future communication
backbones which interconnect sensors and actuators with ECU in cars will be
built on Ethernet technologies. However, signalling from different application
domains demands for network services of tailored attributes, including
real-time transmission protocols as defined in the TSN Ethernet extensions.
These QoS constraints will increase network complexity even further.
Event-based simulation is a key technology to master the challenges of an
in-car network design. This chapter introduces the domain-specific aspects and
simulation models for in-vehicular networks and presents an overview of the
car-centric network design process. Starting from a domain specific description
language, we cover the corresponding simulation models with their workflows and
apply our approach to a related case study for an in-car network of a premium
car
Combined automotive safety and security pattern engineering approach
Automotive systems will exhibit increased levels of automation as well as ever tighter integration with other vehicles, traffic infrastructure, and cloud services. From safety perspective, this can be perceived as boon or bane - it greatly increases complexity and uncertainty, but at the same time opens up new opportunities for realizing innovative safety functions. Moreover, cybersecurity becomes important as additional concern because attacks are now much more likely and severe. However, there is a lack of experience with security concerns in context of safety engineering in general and in automotive safety departments in particular. To address this problem, we propose a systematic pattern-based approach that interlinks safety and security patterns and provides guidance with respect to selection and combination of both types of patterns in context of system engineering. A combined safety and security pattern engineering workflow is proposed to provide systematic guidance to support non-expert engineers based on best practices. The application of the approach is shown and demonstrated by an automotive case study and different use case scenarios.EC/H2020/692474/EU/Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems/AMASSEC/H2020/737422/EU/Secure COnnected Trustable Things/SCOTTEC/H2020/732242/EU/Dependability Engineering Innovation for CPS - DEIS/DEISBMBF, 01IS16043, Collaborative Embedded Systems (CrESt
An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development
In this paper, we investigate model-driven engineering, reporting on an
exploratory case-study conducted at a large automotive company. The study
consisted of interviews with 20 engineers and managers working in different
roles. We found that, in the context of a large organization, contextual forces
dominate the cognitive issues of using model-driven technology. The four forces
we identified that are likely independent of the particular abstractions chosen
as the basis of software development are the need for diffing in software
product lines, the needs for problem-specific languages and types, the need for
live modeling in exploratory activities, and the need for point-to-point
traceability between artifacts. We also identified triggers of accidental
complexity, which we refer to as points of friction introduced by languages and
tools. Examples of the friction points identified are insufficient support for
model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe
Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles
The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has
received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking
received support from the European Union’s Horizon 2020 research and innovation programme and Germany,
Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy,
Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL
Joint Undertaking under grant agreement No. 692455-2
Safety-related challenges and opportunities for GPUs in the automotive domain
GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with the emphasis in ISO 26262 functional safety requirements.Authors would like to thank Guillem Bernat from Rapita Systems for his technical feedback on this work. The research leading to this work has received funding from the European Re-search Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773). This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Carles Hernández is jointly funded by the Spanish Ministry of Economy and Competitiveness and FEDER funds through grant TIN2014-60404-JIN.Peer ReviewedPostprint (author's final draft
Ethernet - a survey on its fields of application
During the last decades, Ethernet progressively became the most widely used local area networking (LAN) technology. Apart from LAN installations, Ethernet became also attractive for many other fields of application, ranging from industry to avionics, telecommunication, and multimedia. The expanded application of this technology is mainly due to its significant assets like reduced cost, backward-compatibility, flexibility, and expandability. However, this new trend raises some problems concerning the services of the protocol and the requirements for each application. Therefore, specific adaptations prove essential to integrate this communication technology in each field of application. Our primary objective is to show how Ethernet has been enhanced to comply with the specific requirements of several application fields, particularly in transport, embedded and multimedia contexts. The paper first describes the common Ethernet LAN technology and highlights its main features. It reviews the most important specific Ethernet versions with respect to each application field’s requirements. Finally, we compare these different fields of application and we particularly focus on the fundamental concepts and the quality of service capabilities of each proposal
Developing a distributed electronic health-record store for India
The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
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