Automated Driving

Design, and Simulate Tomorrow’s Automated Driving

Automated Driving is a driving technology that can percept the surrounding environment and move without any human intervention.

MATLAB and Simulink enable automotive engineering organizations to accelerate vehicle development processes and to deliver vehicles that meet market requirements for safety, comfort, fuel economy, and performance.

Automotive engineers use MATLAB and Simulink to:

  • Run simulations to evaluate trade-offs and optimize designs
  • Develop and test perception, planning, and control algorithms
  • Validate requirements early through rapid prototyping
  • Generate code for prototyping or production, in floating or fixed-point, for MCUs, GPUs, SoCs and FPGA devices
  • Analyze test fleet and production vehicle data
  • Comply with AUTOSAR and ISO 26262 standards

Model-based Design Solutions in the Automotive Industry e-book

Automated Driving and Advanced Driving Assistance Systems (ADAS)

Use MATLAB and Simulink to accelerate the development of automated driving functions including perception, planning, and control functions.

Run simulations in Simulink to test, integrate, and tune these functions using programmatically generated scenes and maximize test coverage across various road, traffic, and environmental conditions without expensive prototype vehicles.

With MATLAB and Simulink, you can:

  • Develop perception systems by predeveloped algorithms, sensor models and apps for computer vision, lidar, radar processing and sensor fusion.
  • Design control systems and model vehicle dynamics in a 3D environment by using fully unified reference apps.
  • Test and verify systems by using synthetic sensor models and writing driving scenarios.
  • Use specific images for autonomous driving.
  • Plan driving routes by designing and using vehicle cost maps and movement planning algorithms.
  • Reduce the necessary engineering efforts to comply with ISO 26262.
  • Generate autonomous C codes for rapid prototyping and HIL test by using code generation products.

Sensor Fusion by Using Synthetic Radar and Vision Data e-book.

Creating In-Loop Real-Time Driver Simulators

In addition to requiring adapt hardware to imitate real and physical driving scenarios, driving simulators / online driving simulators involve complex physics and mechanics. When you add ADAS and autonomous driving features to these already-complex systems, it becomes necessary to test multiple scenarios via in-loop driver simulators before deploying control algorithms to roads.

This online seminar provides an overview of MathWork’s vehicle dynamics simulation offers and then explains how to transition from desktop simulation to real-time in-loop simulation.

Creating In-Loop Real-Time Driver Simulators online seminar.

10 Best Practices to Develop AUTOSAR using Simulink Guide

Develop AUTOSAR ECU software while minimizing cost, risk, and disruptions. Simulink® provides AUTOSAR capabilities as well as APIs for workflow automation.

Based on extensive practical experience helping automotive companies and OEM suppliers, MathWorks consultants have identified 10 best practices for AUTOSAR deployment with Simulink and Model-Based Design.

10 Best Practices to Develop AUTOSAR using Simulink Guide

Download guide to learn about;

  • Defining strategies for migrating Simulink models to AUTOSAR: clean sheet, complete migration, and model variants
  • Selecting a data management strategy (Simulink, AUTOSAR Authoring Tool, or external tool) and establishing a modeling standard for AUTOSAR adoption
  • Simulating and automatically generating code for both AUTOSAR and non-AUTOSAR targets from the same Simulink models
  • Actively planning for evolving AUTOSAR and ISO 26262 standards.