White paper

Integrating Hardware/Software Development for Autonomous Vehicles

Autonomous vehicle development demands an engineering environment that integrates hardware (including mechanical and electrical/electronics) and software development processes. Siemens provides a toolset and ecosystem that is integrated where it needs to be and independent where necessary.

Among the technical domains where Siemens offers autonomous driving-related solutions:

  • Low-power, high performance system-on-chip development with pre-silicon validation
  • Autonomous driving compute platform emulation with form-factor configuration for sensor fusion and low-power consumption
  • Embedded software development, automation, testing and release management
  • Control algorithms for machine learning, sensor fusion and path planning
  • Sensor development for automotive environment and performance optimizations
  • Integration of complex electrical subsystems considering sensor durability and reliability
  • Optimization of electrical/electronics (EE) vehicle architectures for distributed software and network communication
  • Validation and verification of autonomous systems at vehicle and occupant level with virtual environments synthesizing millions of real-world scenarios with digital twins to ensure regressive and rare safety-critical test coverages.

Read more in this whitepaper by Piyush Karkare, Director of Global Automotive Industry Solutions at Siemens PLM Software.

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Autonomous vehicle development demands an engineering environment that integrates hardware (including mechanical and electrical/electronics) and software development processes. Siemens provides a toolset and ecosystem that is integrated where it needs to be and independent where necessary.

Among the technical domains where Siemens offers autonomous driving-related solutions:

  • Low-power, high performance system-on-chip development with pre-silicon validation
  • Autonomous driving compute platform emulation with form-factor configuration for sensor fusion and low-power consumption
  • Embedded software development, automation, testing and release management
  • Control algorithms for machine learning, sensor fusion and path planning
  • Sensor development for automotive environment and performance optimizations
  • Integration of complex electrical subsystems considering sensor durability and reliability
  • Optimization of electrical/electronics (EE) vehicle architectures for distributed software and network communication
  • Validation and verification of autonomous systems at vehicle and occupant level with virtual environments synthesizing millions of real-world scenarios with digital twins to ensure regressive and rare safety-critical test coverages.

Read more in this whitepaper by Piyush Karkare, Director of Global Automotive Industry Solutions at Siemens PLM Software.

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