ADAS and AD development platform

Develop, test, and validate advanced driver-assistance systems (ADAS) and automated driving (AD) systems with confidence. Increase development speed, safety, and system quality with Applied Intuition’s development platform.
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“Applied Intuition’s solution allows us to highly automate our scenario-based, data-driven engineering workflows and adapt jointly developed applications as white-box solutions for the overall management of high-performance, safety-critical AD systems.”
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Gero Kempf
Executive Vice President for ADAS/AD
“The Applied Intuition team has demonstrated their expertise and has equipped us with tools to accelerate the safe development of commercial trucks in a financially viable way.”
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Michael Fleming
Founder and Board Member
“We chose to work with Applied Intuition because of its state-of-the-art simulation technology. We are comprehensively validating our system for various complex situations that could arise in the real world.”
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Takao Asami
Senior Vice President
“Applied Intuition works hand in hand with our engineering teams to integrate their tools with our quite complex codebase.”
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Nikos Michalakis
VP of Software Platform

Challenges

The deployment of complex ADAS and AD software can pose significant challenges for leading automakers, who need to cost-effectively and scalably develop and validate these systems. Real-world testing and data collection can be expensive and unsafe.
Siloed processes and disparate workflows
Delayed development timelines
Safety risks in production software

Approach

Applied Intuition’s development platform allows engineering teams to safely develop and test ADAS and AD systems at scale. The unified toolchain spans across the entire development cycle, from simulation to data exploration and validation. It uses machine learning (ML) techniques to support increasingly realistic and complex use cases.
Deterministic and highly scalable simulations
Constantly evolving ML-based components
Unified workflows for faster, safer ADAS and AD development

The ADAS and AD development cycle

Collect and generate data

Obtain drive logs through real-world testing. Automatically search and identify relevant real-world drive logs for re-simulation, training, or evaluation with our auto-curation models. Generate synthetic data designed to improve autonomy systems for cases where real-world data collection is expensive, difficult, or dangerous.

Create scenarios

Create synthetic scenarios for perception, prediction, planning, and controls simulation. Our sensor and object-level simulators are deterministic and realistic, easy to use, and able to integrate with all systems under test. Complement synthetic scenarios with re-simulations of real-world drive logs. Use generative techniques to create complex scenarios that are difficult to build by hand.

Run simulations

Intelligently select and run thousands of simulations in parallel, either on-premise or in the cloud. Perform automatic progression and regression tests before every code change is merged. Simulate autonomous vehicle performance with accurate, detailed, and efficient vehicle dynamics models.

Analyze and validate

Visualize test results in user-friendly dashboards. Assess system performance and track coverage for an operational design domain (ODD). Ensure functional, system, and regulatory requirements are met before integrating software modules into the overall vehicle architecture.

Explore the products

Simulation products

Object Sim

Simulator for planning, prediction, and controls development
ISO 26262-certified simulator with a rich library of behaviors for vehicles, pedestrians, and other agents for realistic object simulation
Flexible, composable library of criteria to determine if a scenario passes or fails
Intuitive and easy-to-use workflows for creating, editing, and managing scenarios at scale
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Sensor Sim

Physically accurate simulator to develop, test, and validate sensor suites and perception systems
Library of validated sensor models to represent specific sensor hardware
Procedurally generated 3D worlds customized to an ODD
Programmatically generated ground truth labels ready for ML systems, such as bounding boxes, depth, semantic segmentation, and optical flow
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Log Sim

Log-based testing tool to identify, reproduce, debug, and resolve issues from real-world testing
Deterministic log data re-simulation to reproduce real-world behavior
Scenario extraction to generate complex synthetic scenarios from vehicle data
Performant web-based playback enabling accurate debugging and root-cause analysis
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Cloud Engine

Execution engine that runs object, sensor, and log simulations at scale in the cloud
Scalable, reliable, and cost-efficient infrastructure for large-scale parallel simulation and integration into continuous integration (CI) pipelines
Cloud-based workflows for simulation at scale, giving the ability to manage scenarios and test libraries, view results, and assess performance collaboratively across an organization
Interoperable and configurable infrastructure to run on AWS, Azure, Google Cloud, and on-premise
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VehicleSim

Comprehensive suite of software tools that enables realistic and dynamic simulation of vehicle behavior
Physically accurate vehicle models designed for use by novices and experts alike
High-performance computing (HPC) for increased coverage, locally and in the cloud
Real-time models ideal for software-in-the-loop (SIL), driver-in-the-loop (DIL), and hardware-in-the-loop (HIL) development
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HIL Sim

Hardware-in-the-loop simulator to identify safety-critical failures early and reduce development time
Object-level HIL testing for planning and controls development
Sensor-level HIL testing to validate a system from sensor input to actuation
Vendor-agnostic approach, supporting all mainstream hardware vendors
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Data products

Data Explorer

Visualization and query tool for collected log data
Cloud-based visualizer to search across logs, root-cause events, and export data
Rule-based ingestion and intelligent models to enrich data with relevant metadata, especially for unlabeled logs
Scalable querying engine to identify important logs
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Synthetic Datasets

Synthetic dataset generation tool optimized to train machine learning (ML) models
High-level dataset definition language and visual editor to easily define needed data
Dataset management tooling to view statistics, filter, and export data
Generated datasets are proven to improve model performance in published case studies
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Validation Toolset

Verification and validation tool to accelerate production deployments safely
Integrate test management artifacts and define an ODD to analyze system performance, measure safety, and improve test coverage
Support for abstract and logical scenario languages such as OpenSCENARIO V2.0 to easily generate scenario variations
Intelligently sample scenario variations to target failure regions and reduce computational execution cost
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Test Suites

Pre-defined scenario suites to comply with regulations and build a safety case
High-quality base scenarios that fit unique requirements and assess performance
Simulate regulatory testing protocols such as Euro NCAP, NHTSA, and more
Complex actor behaviors, routes, trigger conditions, and observers to run simulation tests out-of-the-box
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Map Toolset

Tool to create maps for use in simulation or on vehicles and generate test cases at scale
Web-based interface to create maps, edit maps, and validate maps
Parameter sweeps over different map attributes to generate scenarios at scale around points of interest
Generate realistic 3D worlds with minimal effort for a target ODD
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Applied Intuition Copilot

A generative AI-powered, prompt-based interface to interact with Applied Intuition’s ADAS and AD development platform
Generate simulation scenarios from simple text prompts
Create and edit maps using natural language prompts
Use natural language to generate SQL prompts
Tag and annotate drive log data automatically for search
Rapidly onboard and learn workflows in Applied Intuition’s ADAS and AD development platform
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Benefits

Accelerate time to market

Easily integrate complex software systems as the industry shifts from hardware-defined vehicles to software-defined vehicles (SDVs). Develop, test, and validate systems continuously to meet production timelines using the latest generative AI techniques.

Ensure ADAS and AD safety

Ensure safety across all dimensions including ODD, requirements, geographic, and scenario metrics. Validate ADAS and AD systems against complex and dangerous situations that could arise in the real world.

Increase productivity

Use a modular platform that supports a variety of formats and environments. Establish flexible processes and meet unique software development needs. Facilitate global collaboration across teams and time zones.

Optimize production costs

“Shift left” with virtual testing such as SIL and HIL to reduce costly on-road tests. Use simulation efficiently to manage data and compute costs with fine-tuned technologies.

Frequently asked questions

What is ADAS?
What is AD?
What are the 6 levels of vehicle autonomy?
What are the key components of an ADAS and AD development platform?
How do simulation tools contribute to the development of ADAS and AD systems?
What role does artificial intelligence (AI) play in the development of ADAS and AD systems?
What types of testing are essential for validating ADAS and AD systems?

Get started with the ADAS and AD development platform

Accelerate your ADAS and AD software development today.
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