Ulrich Wurstbauer & Mohamed Nassar
How to develop an autonomous car end-to-end: Robotic Drive and the mobility revolution
#1about 12 minutes
Overview of DXC Loft's automotive solutions and expertise
The company provides end-to-end automotive solutions, including autonomous drive and digital cockpit, for major OEMs and tier-one suppliers.
#2about 3 minutes
Understanding the disruptive shift to high-level vehicle autonomy
Moving from driver-assist (Level 2) to full autonomy (Level 3+) requires a massive increase in R&D investment and a shift to data-driven development.
#3about 11 minutes
Managing massive data scales with the Robotic Drive platform
The Robotic Drive solution uses a geo-distributed data lake and containerized computing clusters to ingest, store, and process petabytes of real-world and virtual driving data.
#4about 13 minutes
Using virtual validation and simulation for scalable testing
Digital twins and gaming engine-based simulations are used to test autonomous functions across billions of virtual miles, covering diverse environmental conditions and edge cases.
#5about 8 minutes
Integrating autonomous software into complex vehicle hardware
Deploying algorithms into the vehicle requires navigating a complex embedded environment with safety-critical microcontrollers, certified operating systems, and standards like ISO 26262.
#6about 29 minutes
The automotive industry's shift to software-centric development
The traditional hardware-centric OEM model is evolving into a software-centric approach where OEMs integrate software from multiple suppliers using rapid CI/CD pipelines.
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Matching moments
04:48 MIN
Overview of the data-driven development lifecycle for cars
Developing an AI.SDK
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10:46 MIN
Defining the architecture and technology for driverless parking
The future of automotive mobility: Upcoming E/E architectures, V2X and its challenges
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02:16 MIN
The multidisciplinary future of automated driving development
Automated Driving - Why is it so hard to introduce
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06:16 MIN
Building an AI-ready architecture for autonomous driving
What non-automotive Machine Learning projects can learn from automotive Machine Learning projects
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08:33 MIN
Exploring real-world automotive use cases from Bosch
On developing smartphones on wheels
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01:00 MIN
Developing the software-defined vehicle (SDV)
Harnessing the Power of Open Source's Newest Technologies
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11:50 MIN
Q&A on tech stack, safety, and testing
Building a hypercar from scratch
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21:16 MIN
Overcoming challenges in automotive software deployment
Intelligent Data Selection for Continual Learning of AI Functions
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