Cognigear
Autonomy Stack Engineering

Simulation, Scenario Library & HIL/SIL Bench Design

Stand up simulation environments, scenario libraries, and HIL/SIL benches for regression and safety testing.

Timeline
8 Weeks to Value
Typical Engagement
$80k–$220k
Focus Areas
All autonomous vehicles

Simulation, Scenario Library & HIL/SIL Bench Design

Stop testing code for the first time on a 300-ton truck. Build a simulation pipeline to validate safety and performance before deployment.

  • Create a "Digital Twin" of your site for risk-free testing
  • Automate regression testing with thousands of scenarios (CI/CD)
  • Validate hardware integration with Hardware-in-the-Loop (HIL) benches

Who this is for

V&V Leads, DevOps Engineers, and Safety Managers at:

  • Autonomy developers needing to scale testing beyond physical hours
  • OEMs ensuring ECU integration robustness
  • Operators wanting to validate vendor updates before fleet-wide rollout

Operational context

This engagement focuses on:

  • Simulators – Unreal/Unity-based (Carla, AirSim), Physics-based (Gazebo, MuJoCo), Commercial (Ansys, MathWorks)
  • Pipeline – Software-in-the-Loop (SIL) cloud scaling, Hardware-in-the-Loop (HIL) physical wiring
  • Scenarios – Edge cases, regression sets, safety violations, random traffic generation

Trigger phrases you might be saying

  • “We broke the truck again testing a new software build.”
  • “We can only test when the mine is shut down.”
  • “How do we know the new update didn't break the old features?”
  • “We need to test unsafe scenarios (like collisions) that we can't do in reality.”

Business outcomes

  • 100x acceleration in testing miles via parallel cloud simulation
  • Reduced physical damage to equipment during development
  • Safety case evidence for regulatory bodies (showing "1 million sim miles")
  • Faster release cycles through automated nightly regression support

What we deliver

  • Simulation architecture strategy (Engine selection, Asset pipeline)
  • Scenario Description Language (OpenSCENARIO) implementation
  • Core scenario library creation (top 50 critical site events)
  • HIL Bench design (rack layout, wiring, ECU integration)
  • CI/CD integration plan

How it works

  1. Asset Creation – Build visual and physics models of the site and vehicles
  2. Infrastructure – Set up the SIL/HIL runners and orchestration
  3. Scenario Design – Define the test cases (e.g., "pedestrian pops out from behind truck")

Timeline & effort

  • Duration: 8-10 weeks
  • Client time: providing vehicle specs, CAD models, and ECU hardware for HIL
  • Data: Site surveys (point clouds) for Digital Twin creation

Pricing bands

Fixed-fee: $80k–$220k, depending on:

  • Fidelity requirements (visual realism vs. physics accuracy)
  • Number of scenarios to author
  • HIL hardware complexity (integrating braking ECUs, steering columns, etc.)

Tech stack & integrations

  • Engines: Carla, LGSVL, Gazebo, Nvidia Isaac Sim
  • Formats: OpenDRIVE, OpenSCENARIO, URDF, SDF
  • HIL Hardware: dSPACE, Speedgoat, National Instruments, Vector CANoe

Risks & safeguards

We explicitly design for:

  • Sim-to-Real gap – ensuring the sim isn't "too perfect" (adding noise/latency)
  • Reproducibility – ensuring bugs found in sim are deterministic
  • Scalability – designing for cloud execution (Docker/Kubernetes) rather than just one desktop
  • Vendor lock-in – favoring open standards for scenario definitions

Site examples

  • Mining Tech Co (Canada) – Built a HIL bench with real braking hydraulics and steering actuators to validate safety controller logic, catching a critical timing bug before track testing.
  • Logistics Startup (USA) – Implemented a cloud-based SIL pipeline running 10,000 randomized intersection scenarios per night to validate a new planner release.

Frequently asked questions

Do we need a full 3D visual sim? Not always. For logic testing, a 2D "stage" simulator is faster and cheaper. We help you choose the right fidelity for the right test.

Can you simulate our sensors? Yes, modern simulators support ray-tracing for LiDAR, Radar, and Cameras, though modeling the "noise" accurately is the hard part.

Who maintains the sim? We build the foundation. We can train your team or provide ongoing "SimOps" support to keep assets and scenarios updated.


Target KPIs

  • Regression test cycle time
  • Scenario library coverage %
  • Sim-to-Real correlation score
  • Bugs found in sim vs. field
  • Hardware utilization

Deployed Environments

Virtual worldsDigital Twins

Ready to start?

Book a 15-minute technical scoping call to discuss your fleet requirements.

Book Scoping Call

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