Pylot

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Pylot is an open-source autonomous vehicle platform for developing and testing components like perception, prediction, and planning. It runs on the CARLA simulator and real-world vehicles, offering various models and controllers.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is pylot?

Pylot is a modular, open-source autonomous vehicle platform designed for the development and testing of autonomous vehicle components. It supports a wide range of functionalities including obstacle detection, traffic light detection, lane detection, obstacle tracking, localization, segmentation, fusion, prediction, planning, and control. The platform can be deployed on the CARLA simulator for virtual testing and also integrated with real-world vehicles. Pylot offers various models for object detection (e.g., frcnn_resnet101, ssd-mobilenet-fpn-640) and multiple planning options (waypoint, Frenet Optimal Trajectory, RRT*, Hybrid A*) and controllers (PID, MPC, simulator auto-pilot). It also provides tools for data collection within CARLA, making it a comprehensive solution for autonomous driving research and development.

Best used for

Ideal for developers and researchers who need to develop and test autonomous vehicle components, simulate driving scenarios, and collect comprehensive data. Especially valuable for experimenting with different perception, prediction, and planning algorithms in a flexible, open-source environment.

Common actions

develop autonomous vehicles

test driving algorithms

simulate vehicle behavior

collect driving data

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Capabilities

Key features

Modular autonomous driving platform
CARLA simulator integration
Real-world vehicle compatibility
Obstacle detection
Traffic light detection
Multiple planning algorithms
Data collection capabilities

Target Audience

developer

Integrations

carla

Pricing & Plans

Open Source

Free

FAQs

What components of autonomous driving can Pylot develop and test?

Pylot supports the development and testing of various autonomous vehicle components, including obstacle detection, traffic light detection, lane detection, obstacle tracking, localization, segmentation, fusion, prediction, planning, and control. Each component can be run in isolation or as part of the full application.

Does Pylot support real-world vehicle integration?

Yes, Pylot is designed to run on both the CARLA simulator and real-world vehicles. This allows for a seamless transition from simulated development and testing to practical application in physical autonomous systems.

Can Pylot be used for data collection?

Pylot includes a script for collecting various types of CARLA data, such as RGB images, segmented images, 2D bounding boxes, depth frames, point clouds, traffic lights, and obstacle trajectories. This data can be used for training and evaluating autonomous driving models.

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