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The use cases for the Connected Vehicle Blueprint are itemized below. For R3, we release the Microservice Platform Tars,  which supports the multiple connected vehicle application deployment/management/orchestration/monitor.

UseCases

value proposition

Accurate Location

The accuracy of location improved by over 10 times than today's system. Today’s  GPS system is around 5-10meters away from your reallocation, <1 meter is possible with the help of edge computing. 

Smarter Navigation

Real-time traffic information update, reduces the latency from minutes to seconds, figure out the most efficient way for drivers.

Safe DriveImprovement

Figure out the potential risks which can NOT be seen by the driver. See below.

Reduce traffic violation

Let the driverunderstand the traffic rule in some specific area. For instance,  change the line prior to a narrow street, avoiding the opposite way drive in the one-way road, avoiding carpool lane when a single driver and so on.


Overall Architecture

The following picture depicts the architecture of the Connect Vehicle Blueprint, which consists of the following key components:

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For R3, we deploy it in inwinSTACK Private LAB for Release.  The detailed hardware is itemized below:

Hostname

Core

RAM

HDD

NIC

Role

Node-0

8

40GB

3TB

1GB

Jenkins Master

Node-1

8

96GB

3TB

1GB

Tars Framework

Node-2

8

96GB

3TB

1GB

Tars Node (CVB + Type4 Application + Virtual Classroom Teacher Client + Virtual Classroom Student Client)


Tars is an edge compute microservice platform with low latency, high quality. 
Notes

Hardware and Software Management

Licensing


Components

Link

License

Akraino Release target

Tars https://github.com/TarsCloud/Tars - v2.0BSD 3-Clause LicenseR3
IEChttps://gerrit.akraino.org/r/#/admin/projects/iec - v3.0Apache License 2.0R3