White paper

Simulation Software for Engineering of Autonomous Heavy Equipment

This white paper considers the benefits of simulation solutions for designers and engineers in the heavy-duty vehicle industry, from conceptualization to realization of autonomous machines.

It discusses the latest progress in the areas of virtual vehicle development and testing, simulated sensor development, creating virtual working environments, and presents how the effective and fluid integration of these simulation technologies has been achieved in Simcenter™ software, which is part of the Xcelerator™ portfolio, the comprehensive and integrated portfolio of software and services from Siemens Digital Industries Software.

MBSE for Heavy Equipment Engineers

Model-based systems engineering (MBSE) is a perfect match for the development of autonomous vehicles. The adoption of simulation allows to development of the digital twin of both the machine as well as its interacting environment. Thus, engineers can virtually explore the autonomous vehicle designs, as well as accelerate advanced control verification and validation, which can be tough for vehicle durability and expensive if pursued using a classical physical testing approach.

Reduce Complexity of Heavy Equipment Engineering with Digital Twin Technology

The development of a comprehensive digital framework to support autonomous heavy equipment development relies on 3 main pillars. First, the machine itself. Second, the natural environment in which the machine operates. Third, the sensors are supposed to replace operators’ senses.

Automate Verification and Validation to Reduce Cost

A key element leading to a significant reduction of the cost of autonomous heavy equipment simulation is the automation of the algorithm verification and validation workflow. Indeed, automating the validation of algorithms performance under various weather or lighting conditions, or simply making sure that the workflow covers all possible scenarios, allows an improved coverage of your perception algorithm validation, not talking about development time and cost-saving associated with this automation.

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This white paper considers the benefits of simulation solutions for designers and engineers in the heavy-duty vehicle industry, from conceptualization to realization of autonomous machines.

It discusses the latest progress in the areas of virtual vehicle development and testing, simulated sensor development, creating virtual working environments, and presents how the effective and fluid integration of these simulation technologies has been achieved in Simcenter™ software, which is part of the Xcelerator™ portfolio, the comprehensive and integrated portfolio of software and services from Siemens Digital Industries Software.

MBSE for Heavy Equipment Engineers

Model-based systems engineering (MBSE) is a perfect match for the development of autonomous vehicles. The adoption of simulation allows to development of the digital twin of both the machine as well as its interacting environment. Thus, engineers can virtually explore the autonomous vehicle designs, as well as accelerate advanced control verification and validation, which can be tough for vehicle durability and expensive if pursued using a classical physical testing approach.

Reduce Complexity of Heavy Equipment Engineering with Digital Twin Technology

The development of a comprehensive digital framework to support autonomous heavy equipment development relies on 3 main pillars. First, the machine itself. Second, the natural environment in which the machine operates. Third, the sensors are supposed to replace operators’ senses.

Automate Verification and Validation to Reduce Cost

A key element leading to a significant reduction of the cost of autonomous heavy equipment simulation is the automation of the algorithm verification and validation workflow. Indeed, automating the validation of algorithms performance under various weather or lighting conditions, or simply making sure that the workflow covers all possible scenarios, allows an improved coverage of your perception algorithm validation, not talking about development time and cost-saving associated with this automation.