Track: Programmable Real-Time Networks |
| Cloud Based Decision Making for an Autonomous Vehicle |
| Autonomous Vehicle is a representative example of real time networks based advanced and intelligent applications. The 5G wireless based Vehicle to Everything (V2X) network utilizes distributed storage and computing capabilities enabled by the Cloud, Mobile Edge Computing (MEC), and (local) vehicle resident computer. This presentation provides the treatment of two scenarios - 1) avoiding accident with a non-moving obstruction or a moving vehicle in front and 2) traffic light handling. The vehicle resident camera and radar fusion is used as the source for sensor data. The brake system is the primary actuator. The algorithms are simulated based on use of one of two resources – onboard computer or the Cloud, thus bounding the analysis for the MEC resource situation. A graphic interface based simulation is implemented for validation and to demonstrate proof of concept for the two scenarios. The simulation module is built using Animation APIs from the Python library Matplotlib. The results between the two options – vehicle based on-board computer and the network cloud are discussed and compared. Pictorial representations of the vehicle as it approaches the target are presented. |
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| Presentation Video |
| Presentation Notes |
| yang-borkar-Autonomus-Vehicle-Decision-Making.pptx |
Real Time Communications Conference & Expo at Illinois Tech
IEEE International Conference
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