Risk Management for Embedded Software Development What do successful downhill skiers, Formula One racers, and mountain climbers have in common? They learn as much as they can about their sport and they use the very best equipment available. By taking this approach, they transform pure risk into calculated risk with tangible payback. But developing embedded software isn’t a dangerous sport, you say… In truth, embedded software development for advanced driver assistance systems (ADAS) and Read Article The Benefits of Tesla Autopilot and How ADAS Will Save Lives Editorial Credit: Nadezda Murmakova / Shutterstock.com What’s the first thing you think about when buying a car? I want wheels that are sexy, speedy, but most importantly, safe. Car wrecks kill around 40,000 people per year in the US, and those numbers may be rising. Low gas prices have more people out on the roads, while bigger and better smartphones have them more distracted. Companies like Tesla are looking to reduce driving deaths with Read Article How Autonomous Cars and Big Data Will Help First Responders It’s a bit strange what things people are afraid of. After watching Shark Week each year I become more and more afraid of sharks, even though I’ve never seen one at the beach. In fact, it’s much more likely that I’d be injured in a car wreck, though I don’t feel any fear each time I get behind the wheel. Whether or not I’m afraid, the risk is still there, though new advances in technology are minimizing that risk. Advanced driver assistance Read Article How Automotive IoT is Shaping Wireless Networks When I bought my car, it was a big deal that it could use bluetooth and sync to my phone for calls and music. The sales guy went on and on about it. I mostly listened to the radio on scan, so this was not a key feature for me, but I’ve come to love the hands-free calling. Last year, my friend bought a newer model of the car, and the bluetooth communication has expanded to maps, Pandora, and other apps. However, they are all still accessed via a Read Article Impediments to the Implementation of Machine Learning Algorithms in Autonomous Vehicles Machine learning is considered to be the next big step for self-driving cars. You may not know, however, that machine learning cars first hit the road decades ago. One notable example is ALVINN, which stands for Autonomous Land Vehicle in a Neural Network. As its name suggests, ALVINN used a neural network to watch a human driver and learn how to drive itself. The project was a great example of the potential of self-driving cars. It also clearly Read Article Take Advantage of Infineon AURIX™ TC3xx Family With the Right Compiler Download PDF Don’t Get Stuck with the Wrong Set of DevTools for TriCore Apps Download PDF Taking the Business Risk Out of ADAS Development Download PDF New Compiler Challenges: Optimized For ADAS Applications Download PDF Optimal ADAS Performance Requires Standards-Based Solutions Download PDF Mitigating Powertrain Control Module Design Challenges Download PDF Standards-based ADAS Compliance Drives Auto Safety Download PDF Embedded Compilers For The Needs Of Today's And Tomorrow's Automotive Industry Download PDF PROGRAMMING THE BOSCH® GTM USING THE TRADITIONAL C ARRAY APPROACH Download PDF Safety Checker Overview Guide Download PDF Selecting The TASKING Tricore Toolset That's Right For You Download PDF Optimizing at Application Scope Download PDF Pagination First page « First Previous page ‹‹ First page 1 … Page7 Page8 Page9 Current page10 Page11 Page12 Next page ›› Last page Last » Load More
