Once the preserve of science fiction, momentum is building behind the development of driverless cars. Semi-automated aids that can take control out of the hands of the driver are already hitting the market, with development on more advanced systems continuing to gather pace.
The autonomy of a vehicle is measured according to six levels, a scale devised by the Society of Automotive Engineers. These levels range from fully manual driving at Level 0 to fully autonomous at Level 5. At this higher level of automation, there will be no need for a human to pay any attention to the vehicle, which will be able to go anywhere and do anything that an experienced human driver would be capable of. Fully autonomous vehicles that reach this level are currently undergoing testing, but most systems currently available in cars are at Level 2, able to control steering and acceleration while a human monitors the environment and is able to take control at any time.
To reach those higher levels of automation, ensuring the safety of the passengers who rely on autonomous systems is of paramount importance. With part of the promise of autonomous driving being the removal of human error, every accident is analysed intensely.
“Safety is key, because this is a hard problem to solve,” said Mitra Sinha, principal program manager of Autonomous Driving Microsoft Azure Cloud at Microsoft. “Humans have so many accidents that we almost take it for granted, but every safety incident with an autonomous vehicle becomes news. And while we see some regional efforts at regulation, there is no worldwide standard. This means that there will be incidents, and that is why we see the emphasis on validation, with both road testing and simulation.”
Validation involves fleets of test vehicles driving hundreds of thousands of miles, either virtually or on real roads, to acquire the data necessary to ensure that a vehicle can react appropriately in any given situation. A wide array of sensors must be attached to the test vehicles, all of which produce massive amounts of data. Automakers must find ways to ingest this data, then find the specific datasets that are of interest. Helping to meet these massive data challenges is where Microsoft sees its role within autonomous development.
“Microsoft’s autonomous journey started alongside the rise in demand for autonomous driving technology enablement in the cloud,” said Henry Bzeih, chief strategy and technology officer for automotive at Microsoft. “With Microsoft’s integrated toolchain, aspiring autonomous driving companies can find an end-to-end cloud solution from data ingestion to the deployment of validated training models in this environment. Furthermore, the Microsoft for Start-ups programme provides access to Microsoft’s top support system, which includes contact with architects and experts, as well as early access to Azure, co-development opportunities and joint customer opportunities for autonomous driving solutions to accelerate the growth of such technology.”
One company that has taken advantage of these capabilities in the development of autonomous driving is Wayve, which is building artificial intelligence which learns from observing human driving via reinforcement learning. The company is using Microsoft Azure to help develop their computer vision system, which can be trained in one city and then driven in another.
“We are excited by the opportunities that Azure will create for Wayve as we push our machine learning to new levels of scale using data from fleets of connected vehicles across the world,” said Alex Kendall, the firm’s CEO.
Moving beyond the vehicle itself, there will be significant data-handling challenges in the linkage of the automotive supply chain, logistics systems and tracking services. These systems are all involved in connecting passenger and freight vehicles in real-time, an essential capability for autonomous driving.
“When it comes to linkage with the automotive supply chain, there are two things that are important,” said Sinha. “One of these is providing an environment for data collaboration which is secure. For example, as an original equipment manufacturer (OEM) working with many different tier one partners, you need to make sure that each of their data is kept separate for intellectual property reasons. On the other side, a tier one partner needs to do the same for data from multiple OEMs.
“The second part of the problem is traceability. Automotive is a highly regulated industry, subject to standards which have clearly defined traceability requirements. You need to be able to trace back to make sure that there is enough coverage, and that responsibility also applies across the supply chain.”
Microsoft can bring its own experience of dramatic DevOps transformation to help automotive companies manage the transition to a more connected, autonomous form of mobility. Daimler, one of the world’s largest manufacturers of cars and trucks, has invested significantly in software development for its vehicles. By developing in Azure, the company has been able to onboard developers in hours rather than weeks, get new ideas underway faster, and attract top talent with a state-of-the-art development environment.
“To be world-class in the software arena, we have to move fast,” said Peter Rothlaender, manager of cloud solutions for Daimler. “By early 2016, we knew that we needed a higher-velocity software development model. That’s when Microsoft introduced us to Azure DevTest Labs, then under development. DevTest Labs provides standardised templates for creating dev/test environments and easy access to all needed tools. Since using Azure DevTest Labs, we’ve seen our developer onboarding process drop from weeks to hours. We can demonstrate that we have modern tools and development environments and have a seat at the table with Microsoft when it comes to pushing Azure to the next level.”
We asked selected Microsoft partners how they are helping to develop the solutions that will accelerate the realisation of autonomous driving. Below are extracts from their responses, which you can read in full from page 67 of the digital edition of the Winter 2020 issue of The Record.
Danny Shapiro, senior director of automotive at NVIDIA, says: “NVIDIA partners with hundreds of vehicle makers, suppliers, sensor manufacturers, mapping companies and start-ups around the world to develop the best solutions for the new world of mobility.”
Luz Mauch, executive vice president of automotive at DXC Luxoft, says: “DXC Luxoft’s unique ability to combine automotive engineering innovation and execution with its global delivery network and cloud operations allows us to accelerate the deployment of autonomous and connected solutions and services throughout the vehicle lifecycle.”
This article was originally published in the Winter 2020 issue of The Record. To get future issues delivered directly to your inbox, sign up for a free subscription.
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