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The use cases for the Connected Vehicle Blueprint are itemized below. For R2, 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 R2, we deploy it in Amazon Web Service for Release. The detailed hardware is itemized below:
CPU+Memory | Drive | Deployment |
8Core * 16G | 15G | Jenkins Master |
8Core * 16G | 10+50G | TarsFramework |
8Core * 16G | 10G +20G | TarsNode + Application |
Beyond of AWS, we deploy it in Ampere POD 1 in CI Lab as well.
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