The automotive software industry has always been synonymous for old compilers, out-dated toolchains and resource constraint hardware. “Only use something which has been proven in-use” most safety engineers would argue. In the past, in a distributed E/E-Architecture, this argument would apply because of a low number of independently functioning electronic control units (ECUs).
Fully embracing Open Source Software means to go beyond simply using it – it means to become an active member of the Open Source community. But how do we get there as a big automotive company? At Daimler, we decided that if we are going to take Open Source seriously, this needs to become deeply ingrained in the company’s “DNA”, away from a strict “we develop our own code” attitude.
Our world is changing, and the change is visible everywhere. More than 50% of the population is living in cities and the cities are growing. More and more goods and people need to be transported, bringing the traffic infrastructure to its limits. Increasing pollution and noise levels bringing the environment to its limits.
To counter this, a transformation of the mobility is needed, who has already started, powered by new technologies and services. The mobility of the future will be electrified, connected, personalized, automated and software defined.
Work in the field of highly automated driving and autonomous mobility introduces a new complexity into the development of embedded systems in vehicles and requires many multi-faceted processes incorporating a variety of software tools. It is necessary to combine existing technologies with new technologies or new tools.
Migration from single to multicore ECU systems are always challenging. One such challenge is ensuring consistent state of shared data among several program components executing on different cores. We have developed an eclipse based eco system to support developers for analyzing such use cases based on Model Driven System Analysis (MDSA). This involves eclipse technologies such as APP4MC, EMF and SIRIUS. This framework combines architecture description with generated code to prepare a base for data consistency analysis.
The Eclipse Kuksa project builds an open ecosystem for connected vehicles as part of the Eclipse IoT working group. The challenges of the automotive domain are addressed with a technology stack that covers the in-vehicle side, a cloud back-end and an online IDE. We provide an update of the current system architecture which makes use of other tools from the Eclipse IoT context. We further demonstrate use-cases so participants get an overview of the potential of Eclipse Kuksa. In addition, we describe how a publicly funded project transitioned to the Eclipse Kuksa project.
Car manufacturers through the application of new technologies such as IOT, Artificial Intelligence, Machine Learning, Telematics and Big data are connecting cars to their network, external and physical infrastructure, building a connected transportation ecosystem.
Eclipse Kuksa project contain a cloud platform that interconnects a wide range of vehicles to the cloud via in-car and internet connections.
The automotive industry is witnessing tremendous ground breaking changes over the decades. The new age vehicles are equipped with more than 200 smart sensors to improve the efficiency and to cater to the ever increasing human demands and needs. With the rapid evolution of technology, self-driving cars no longer seem like a farfetched dream but something that can soon be mastered.
Vehicle-to-Cloud connectivity is opening up a vehicle’s internal resources such as data and functions to the outside world. This generates new opportunities by creating innovative customer services that enable new business models and technologies. However, current IoT technologies do not yet fully support automotive needs.
Teaser: Today, the development of automotive software functions based on artificial intelligence still needs a lot of different tools, languages and frameworks.
In this talk, we introduce how we built upon the Eclipse eco-system an integrated development environment called "DAISY" (Development environment for Artificial Intelligence SYstems).
