README.md

AutoCore SDV Project

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:

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

• Host:

  • Host PC:
    • CPU: x86_64 4 Core or above
    • RAM: 8G+
    • Disk: 30G+ free space
    • OS: Ubuntu 18.04+
    • cable Ethernet

• For each Worker (default sets 2 workers in cluster):

  • AutoCore PCU

    • Flash images from Release for k8s install

    • cable Ethernet

      OR

  • Worker PC (Needs when you don't have AutoCore PCU):

    • CPU: x86_64 8 Core or above
    • RAM: 8G+
    • Disk: 30G+ free space
    • OS: Ubuntu 18.04+
    • cable Ethernet

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. AutoCore PCU OR Worker PC:

• $ source Utils/setup/k8s/worker/setup.bash

• $ sudo kubeadm join xxx

  Please find the xxx in the concole output of Host PC as described in step 1.

1. Back to Host PC

• For each worker node, label them:

  $ kubectl label node <worker_node_name> app=autoware

Deploy workloads with config file

Default configs 2 workers in cluster, and if you have two works hardware, just run the default command:

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

And if you have other custom deployment, Just download sdv_demo.yaml and fix the replicas: 2 to your worker count N:

spec:
- replicas: 2
+ replicas: N
  selector:

then use this config file:

$ kubectl apply -f sdv_demo.yaml

Use CloudViewer to display scene and send commands.

Open CloudViewer with Chromium based browser

• Config IP Address to Host PC IP (defaults 127.0.0.1)

• Move viewer with key WSAD and mouse midde and right key.

• Click on vehicle and traffic light to inspect and send commands.

Video tutorial