The AI car computer called Drive PX will be combined with German automotive supplier ZF's self-driving platform in a fleet test planned by package delivery and logistics vendor Deutsche Post DHL Group (DPDHL). The goal is solving one of the biggest challenges for automating package delivery: getting deliveries the "last mile" between a central location to their final destination. The 2018 demonstration will use the package delivery company's (ETR: DPW) fleet of 3,400 electric delivery vehicles outfitted with cameras, radar and lidar (light detection and ranging). Sensor data is fed into an AI platform based on Drive PX. The partners claimed the combination can leverage AI and deep learning to allow autonomous vehicles to understand its surroundings, plot and drive along a safe route, and then park itself at the delivery point.
Apple has been low key about it autonomous car tech, dubbed Project Titan, but there is now a short video of the iPhone company's self-driving efforts. Voyage co-founder MacCalister Higgins posted a short video of Project Titan's test Lexus SUV, which he called "The Thing." The video givies the public a glimpse of what Apple is up to. The top of the white vehicle is equipped with a suite sensors and self-driving hardware. Higgins said on Twitter the front and back both have 6 LiDARS and that the "majority of the compute stack is likely located inside the roof unit."
Heavy rain and blizzards aren't the only forms of severe weather Waymo's self-driving vehicles encounter on the regular. In a blog post published this morning, the Alphabet subsidiary laid out the ways its cars in over 25 cities tackle fog, dust, smoke, and other dangerous conditions that trip up even human drivers. "Challenging [environmental] conditions, which affect human driver and vehicle performance, are one of the leading contributors to crashes on our roads … Poor perception creates significant risk for other road users including pedestrians, cyclists, and other vehicle occupants," wrote Waymo chief safety officer Debbie Hersman. "Waymo is working hard to master a variety of weather scenarios as part of our mission to improve road safety." To this end, Waymo says its autonomous vehicles are designed to detect sudden extreme weather changes, such as a snowstorm, that could impact their ability to drive safely.
While camera and LiDAR processing have been revolutionized since the introduction of deep learning, radar processing still relies on classical tools. In this paper, we introduce a deep learning approach for radar processing, working directly with the radar complex data. To overcome the lack of radar labeled data, we rely in training only on the radar calibration data and introduce new radar augmentation techniques. We evaluate our method on the radar 4D detection task and demonstrate superior performance compared to the classical approaches while keeping real-time performance. Applying deep learning on radar data has several advantages such as eliminating the need for an expensive radar calibration process each time and enabling classification of the detected objects with almost zero-overhead.
Nowadays, almost every automaker possesses considerable resources to develop self-driving technology for cars, which is the next big step for the automotive industry. The market for autopilot technology is clearly huge, which is evident by an estimation, that approximately 100 million "connected" cars with the capacity of self-driving will be shipped in 2021. While most auto manufacturers try to invent their own solutions, they will be forced to collaborate with technology companies in fields of both software and hardware to bring self-driving cars to roads. Therefore, in this article I provide a list of the most promising publicly traded tech corporations which should be considered by investors who would like to try to profit from the development of autonomous driving. First of all, let us very briefly look at the technology.