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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Cognata provides comprehensive simulation solutions for the entire product lifecycle aimed at developers of ADAS and autonomous vehicles. Their platform features automatically generated 3D environments along with realistic AI-driven traffic agents, making it ideal for AV simulation. Users benefit from a readily available library of scenarios and an intuitive authoring tool to create countless edge cases for autonomous vehicles. The system allows for seamless closed-loop testing with straightforward integration. It also offers customizable rules and visualization options tailored for autonomous simulation, ensuring that performance is both measured and monitored effectively. The digital twin-grade 3D environments accurately reflect roads, buildings, and infrastructure, down to the finest details such as lane markings, surface materials, and traffic signals. Designed to be globally accessible, the cloud-based architecture is both cost-effective and efficient from the outset. Closed-loop simulation and integration with CI/CD workflows can be achieved with just a few clicks. This flexibility empowers engineers to merge control, fusion, and vehicle models seamlessly with Cognata's comprehensive environment, scenario, and sensor modeling capabilities, enhancing the development process significantly. Furthermore, the platform's user-friendly interface ensures that even those with limited experience can navigate and utilize its powerful features effectively.

Description

Parallel Domain Replica Sim empowers users to create highly detailed, fully annotated simulation environments using their own captured data, such as images, videos, and scans. With this innovative tool, you can achieve near-pixel-perfect recreations of actual scenes, effectively converting them into virtual settings that maintain their visual fidelity and realism. Additionally, PD Sim offers a Python API, allowing teams focused on perception, machine learning, and autonomy to design and execute extensive testing scenarios while simulating various sensor inputs like cameras, lidar, and radar in both open- and closed-loop modes. These simulated sensor data streams come fully annotated, enabling developers to evaluate their perception systems across diverse conditions, including different lighting, weather scenarios, object arrangements, and edge cases. This approach significantly reduces the need for extensive real-world data collection, facilitating quicker and more efficient testing processes. Ultimately, PD Replica not only enhances the accuracy of simulations but also streamlines the development cycle for autonomous systems.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Microsoft 365
NVIDIA DRIVE
Python

Integrations

Microsoft 365
NVIDIA DRIVE
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cognata

Country

Italy

Website

www.cognata.com

Vendor Details

Company Name

Parallel Domain

Founded

2017

Country

United States

Website

paralleldomain.com/product

Product Features

Simulation

1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling

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