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Blueprint overview/Introduction

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UseCases

value proposition

Smarter Navigation

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

Safe Drive Improvement

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

Reduce traffic violation

Let the driver understand 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 car pool lane when a single driver and so on.

Cooperative vehicle  and

infrastructure system

Real time road objects status is obtained by roadside sensing system.  Based on the sensing data, the vehicle obtains the traffic warning and driving assistance informationwhich threatens itself.

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Test case: The roadside camera recognizes the vehicles and pedestrians on the road through the edge computing server, and then pushes the pedestrian warning to the host vehicle (blue vehicle) .


Overall application Architecture

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

  • Commodity Hardware, Arm/X86 Physical Server.
  • Virtualization Layer.
  • Tars Microservice Platform layer.
  • Connected Vehicle Applications layer.

Image Added

Connected Vehicle Applications include roadside traffic situation monitoring, driving risk assessment, road event perception, high percision positioning, and so on.

Overall deployment Architecture

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

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Connected Vehicle Applications are some different applications that fulfill Accurate Location, Smarter Navigation, Safe Drive Improvement and Reduce , Reduce traffic violations, and cooperative vehicle infrastructure system.

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Platform Architecture

Software Platform Architecture

The following is the general architecture of Tars, which is a major component in R4.

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Refer to the enclosed PDF document for the detail Tars introduction. 

Image Modified PDF

Main Progresses for Release 4

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Connected Vehicle Blueprint can be flexibly deployed in Bare Metal, Virtual Machine as well as the container.

For R3R4, we deploy it in inwinSTACK Private Intel Pod1 Akraino  LAB for Release.  The detailed hardware is itemized below:

Hostname

Core

RAM

HDD

NIC

Role

Node-0

8

40GB

3TB

1GB10GB

Jenkins Master

Node-1

8

96GB

3TB

1GB10GB

Tars Framework 2.4.13

Node-2

8

96GB

3TB

1GB10GB

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

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Components

Link

License

Akraino Release target

Tarshttps://github.com/TarsCloud/Tars/releases/tag/v2.4.13BSD 3-Clause LicenseR4
IEChttps://gerrit.akraino.org/r/#/admin/projects/iec - v3.0Apache License 2.0R4

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