Perception and localization

Use simulation, re-simulation, and synthetic data to inform advanced driver-assistance systems (ADAS) and automated driving (AD) decision-making.
See the workflow
“We use the most powerful and flexible simulation platforms in the self-driving industry.”
Mike Carter
Founding Engineer

Customer challenge

Testing ADAS and AD perception and localization systems in the real world is time-consuming and often difficult to execute and repeat at scale.
Real-world operations don’t capture all situations
One situation has many edge cases and variations
Certain events are dangerous to test in the real world
Collecting and labeling real datasets is costly

Applied Intuition’s solution

Applied Intuition’s solution allows teams to test ADAS and AD perception and localization systems at scale, identify edge cases, and ensure high-quality code.
Re-simulate failures found in the field
Generate synthetic datasets to train perception models
Utilize sensor simulation to iterate rapidly

Develop high-performing perception and localization systems

01

Identify issues found in field testing

Search real-world logs to identify segments that challenged your ADAS or AD stack, including issues like driver interventions.
02

Perform root cause analysis

Re-simulate the identified real-world logs to understand your ADAS or AD stack’s performance and determine necessary adjustments.
03

Improve and test perception modules

Modify perception modules or re-train machine learning (ML) models with synthetic data to address the identified issues. Iteratively run sensor simulations to monitor progress across purpose-built test cases, and introduce variations across behaviors, weather, and lighting to ensure robustness.
04

Scale testing to ensure safety

Execute a full test suite before merging changes or deploying a new stack version in the field to prevent regressions.

Develop high-performing perception and localization systems

01

Identify issues found in field testing

Search real-world logs to identify segments that challenged your ADAS or AD stack, including issues like driver interventions.
02

Perform root cause analysis

Re-simulate the identified real-world logs to understand your ADAS or AD stack’s performance and determine necessary adjustments.
03

Improve and test perception modules

Modify perception modules or re-train machine learning (ML) models with synthetic data to address the identified issues. Iteratively run sensor simulations to monitor progress across purpose-built test cases, and introduce variations across behaviors, weather, and lighting to ensure robustness.
04

Scale testing to ensure safety

Execute a full test suite before merging changes or deploying a new stack version in the field to prevent regressions.

Speed up your software development life cycle

Prioritize ADAS and AD development

Triage log data quickly to focus on important development tasks.

Escape real-world constraints

Test safety-critical situations and edge cases without real-world constraints.

Iterate faster

Use simulation to reduce the delays and costs of real-world testing.

Get started with perception and localization

Learn how Applied Intuition can help your team develop high-performing ADAS and AD perception and localization systems.
Contact us