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The Eclipse foundation is hosting the OpenADx initiative, encouraging companies to collaborate on integrating different technologies and tools to accelerate the development of Autonomous Driving. This OpenADx initiative is initially being focussed around different testbeds.
Modeling and simulation is becoming a key development methodology for smart and safe systems containing integrated software, hardware, and communication components, interacting with physical (and social) environments. Simulation promises to provide early feedback on critical design decisions.
Defining DSLs in the Eclipse universe has become almost a normal thing and there are incredible frameworks out there to do that. Some of them are textual, others are graphical and from time to time there comes a flood of different attempts to mix both notations. The story of mixed notations is old, yet still not solved in a common way that has proven to be “the solution”. Of course there are plenty of interesting technical challenges, but let’s step back and rethink who is our target audience to see if we are solving a real problem.
Code formatting is an opinionated beast. It always has been a matter of taste, and it always will be a matter of taste. This is the reason, why professional formatting tools, such as Eclipse JDT, offer a gazillion number of options. Which is still not sufficient enough. After all, you can override them inline with tag-comments to make the formatter shut up. Can't we do better than that? What if we could use machine learning techniques to detect the preferred code style that was used in a codebase so far? Turned out, we can.
The Trace Compass project has been providing trace analysis and visualization tools for many years. Analyzing Linux based systems has been one of the main focuses. Call Graph analysis for profiling of applications, analysis of real-time systems or analysis of traces coming from Jaeger (Open Tracing API) are some recent developments for Trace Compass. Moving the UI to modern front-end technologies and showing the analysis results in a web browser is ahead of us.
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.
One challenge the Bosch Autonomous Driving division faces is the toolchain for developing autonomous driving solutions becoming more complex by every level of automation. Well established tools are not well integrated for the use cases and it is easy to detect gaps in the overall toolchain. Instead of solving these challenges alone, wasting lots of money on the path, the Bosch division together with partners from the industry and related domains build up a community to solve the toolchain challenge together in the OpenADx ecosystem.
While voice interaction has become very widespread for the smart home, a typical nerd prefers sticking the keyboard for inter-personal communication. Chatbots are a great way between those two approaches: They can be used like an instant messenger and voice input/output is an option, but not mandatory.
Despite being severly allergic to sunlight the average nerd in all of us sometimes needs to change her location. Of course she will never do so without simulating her path through the physical world in advance and predict possible disturbances on the road ahead. Furthermore, as so many of us are part of the "quantify yourself" movement aiming to optimize your life, the nerd is also keen to optimize the use of newly invented transport modes, like ridepooling, ridesharing or even podcars - but what is the best choice?