Abstract
We study scalability of machine learning environments in the context of mixed collaborative driving. Mixed collaborative driving includes both human controlled vehicles and vehicles controlled by AI (Artificial Intelligence) that share the physical road resources (e.g., intersections and roundabouts). Many such driving situations cannot be easily created nor replicated in the real life. Therefore, development and testing of AI systems is often done with simulators.
Machine learning environments must maintain a real-time understanding of their traffic situation. Scaling of the machine learning environment to multiple distributed nodes is required to support larger number of participating vehicles. Our experimental environment consists of the CARLA simulator, custom AI implemented with the TensorFlow framework, and a corner casesearch subsystem. With the corner case search subsystem we can automatically evaluate the AI in different driving scenarios. In this paper, we present how scaling of the envinronment tomultiple distributed nodes affects its performance.
Machine learning environments must maintain a real-time understanding of their traffic situation. Scaling of the machine learning environment to multiple distributed nodes is required to support larger number of participating vehicles. Our experimental environment consists of the CARLA simulator, custom AI implemented with the TensorFlow framework, and a corner casesearch subsystem. With the corner case search subsystem we can automatically evaluate the AI in different driving scenarios. In this paper, we present how scaling of the envinronment tomultiple distributed nodes affects its performance.
Original language | English |
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Title of host publication | Proceedings - 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019 |
Publisher | IEEE |
Pages | 687-692 |
Number of pages | 6 |
ISBN (Electronic) | 9781728129273 |
DOIs | |
Publication status | Published - 2019 |
MoE publication type | A4 Article in a conference publication |
Event | IEEE International Conference on Industrial Informatics - Aalto University, Helsinki and Espoo, Finland Duration: 22 Jul 2019 → 25 Jul 2019 Conference number: 17 https://www.indin2019.org/ |
Publication series
Name | IEEE International Conference on Industrial Informatics (INDIN) |
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Publisher | IEEE |
ISSN (Print) | 1935-4576 |
Conference
Conference | IEEE International Conference on Industrial Informatics |
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Abbreviated title | INDIN |
Country/Territory | Finland |
City | Helsinki and Espoo |
Period | 22/07/2019 → 25/07/2019 |
Internet address |
Keywords
- Simulation
- Hybrid Systems
- New Control Applications