Using MATLAB on Apache Spark for ADAS Feature Usage Analysis and Scenario Generation
Sanjay Abhyankar, Ford
In the past, engineers download terabyte-sized ADAS datasets to look for edge cases. This approach consumes huge amount of network bandwidth and local storage space. We created a new and more efficient way, which utilizes MATLAB to access Apache Spark resources to decode, analyze data, and search for edge cases right on the Hadoop file system. It dramatically improves throughput and reduces the amount of data downloaded to the engineer’s workstation.
This approach was successfully used to analyze ADAS feature usage from the CAN traffic on Ford’s Big-Data-Drive fleet of vehicles. It will be deployed for all future Big-Data-Drive vehicle analysis.
Published: 16 Nov 2020
Featured Product
Vehicle Network Toolbox
Up Next:
Related Videos:
您也可以从以下列表中选择网站:
如何获得最佳网站性能
选择中国网站(中文或英文)以获得最佳网站性能。其他 MathWorks 国家/地区网站并未针对您所在位置的访问进行优化。
美洲
- América Latina (Español)
- Canada (English)
- United States (English)
欧洲
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
亚太
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)