BMW is driving toward autonomous vehicles with help from a data analytics platform it developed and a partnership with IT services company DXC Technology.
The German-based luxury car company has collected about five million kilometers (3.1 million miles) of real-life driving data from its fleet of test vehicles through its BMW Group High Performance D3 platform, which went live in March. BMW is using DXC’s infrastructure to more rapidly collect, store and manage data from vehicle sensors, which both companies said is resulting in faster autonomous driving development cycles.
BMW is also using DXC’s infrastructure to create apps, including a simulation environment that can help develop functionality for autonomous vehicles, such as the ability to stay in a lane, change lanes, and enter or leave a highway, said Felix Klanner, senior expert on data driven development at BMW Group.
“We’re developing algorithms in two-week sprints, and every two weeks we develop a new feature, test it end to end, and we’re doing the whole environment in simulation,” Klanner said.
Collecting and analyzing autonomous vehicle data
Simulation is the first phase in BMW Group’s three-pronged approach to autonomous vehicle development. The next phase involves testing an autonomous vehicle feature in an internal “hardware-loop environment” and then with a “real feed” on the road, Klanner said. Hardware in the loop refers to control units placed inside the vehicle to collect information such as environmental perception, steering, braking and acceleration.
Data collection has been extended from BMW Group’s development environment in Munich to North America and other parts of Europe, he said.
From all the road travel data ingested into the D3 platform, “two million kilometers (1.25 million miles) of the most relevant driving data and environmental factors are then identified and extracted,” said Dirk Schürmann, vice president and managing director of Germany/North and Central Europe, at DXC.
“Using DXC’s solution, BMW is able to expand the recorded driving data by a further 240 million kilometers (150 million miles) of simulation-generated data, necessary for road approval,” he said.
Revving up the autonomous vehicle development process
DXC set up and runs the data center and develops applications to support the autonomous driving development process, according to Schürmann. “The aim is to reduce costs and the time needed until the system is ready to [go to] market.”
For this project, “We have adapted our working model and have started to [deploy] an Agile development model,” Klanner said, explaining that officials found the traditional model of development to be “too slow and not as powerful.”
The data is also being used to see how the vehicles perform during normal driving situations, such as on a highway and in daylight, as well as in challenging situations, such as when the car has to brake suddenly, he said.
Officials are carefully analyzing the real measurement data and extracting scenarios from both normal and challenging driving situations, he said. Then the data is being ported to the simulation environment with the infrastructure so it can be analyzed step by step, he said. That way, “we can really ensure all the situations which occur on real roads have been taken into account in our development process.”
The combination of the test data and the knowledge BMW officials have gained from real test drives has been important for showing them different situations that autonomous vehicles would have to handle, Klanner said.
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