Skip to content

drcwr/SDV

Repository files navigation

AutoCore SDV Project

Logo

For business and partnership, please visit our website: www.autocore.ai.

Table of Contents

  1. Overview
  2. Quick Start Guide

Overview

SDV (Software Defined Vehicle) project is a cooperative project between Autocore and Futurewei, which aims at providing the technology-consulting services by means of this 100 percent open source software stack with reference design for SDVs. Cloud-Edge service is also integrated as a part of this project to extend the V2X capabilities.

The SDV software stack is based on open source Autoware/ROS2/DDS and Zenoh, where DDS/Zenoh act as the E2E Vehicle-Edge-Cloud middleware layer for the SDV platform. Thru the integration with Futurewei’ s open source KubeEdge project, the SDV platform will leverage Cloud Native Ecosystem tools to provide management, monitoring and software LCM (Life-Cycle-Management) functions.

The system architecture of SDV platform project is shown in the figure below:

Architecture

The software modules in host container runtime are as follows:

And the PCU Container runtime acts as the Domain controller in vehicle with the following software modules:

Quick Start Guide

Hardware requirement

  1. Host PC:
  • CPU: x86_64 3 Core or above
  • RAM: 8G+
  • OS: Ubuntu 18.04+
  • cable Ethernet
  1. Autoware PC:
  • CPU: x86_64 8 Core or above
  • RAM: 16G+
  • Disk: 30G+ free space
  • OS: Ubuntu 18.04+
  • cable Ethernet
  1. PCU clients x N

Environment setup

  1. Host PC:
  • $ source Utils/setup/k8s/control-plane/setup.bash
    Concole will output the information like "kubeadm join xxx", please use this information for clients to join in later steps.
  1. Autoware PC:
  • $ source Utils/setup/k8s/worker/setup.bash
  • $ kubeadm join XXX
    Please find the "xxx" in the concole output of Host PC as described in step 1.
  1. PCU:
  • $ source Utils/setup/k8s/worker/setup.bash
  • $ kubeadm join XXX
    Please find the "xxx" in the concole output of Host PC as described in step 1.

Deploy workloads with config file

kubectl apply -f https://raw.githubusercontent.com/autocore-ai/SDV/preview/sdv_demo.yaml

Use CloudViewer to display scene and send commands.

Just open CloudViewer

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Packages

 
 
 

Languages

  • Shell 100.0%