
Andrew Fortier developed two analytics toolkits for the usdot-fhwa-stol/carma-analytics-fotda repository, focusing on data-driven evaluation of vehicle platooning and PCAP data quality. He built a Python-based IHP2 Data Analysis Toolkit to process ROS1 bag files, enabling visualization of vehicle speeds and gaps for multi-vehicle scenarios, and included shell scripts for dependency management and data preparation. In a subsequent effort, Andrew delivered a PCAP Analysis Toolkit, adding Bash and Python scripts to streamline PCAP file analysis and improve decode reporting. His work emphasized reproducibility, onboarding ease, and actionable insights, demonstrating depth in data analysis, Python scripting, and ROS integration.

June 2025 monthly summary for carma-analytics-fotda: Delivered the PCAP Analysis Toolkit to enable faster PCAP data analysis and improved decoding visibility, driving faster troubleshooting and data quality assessment. This work enhances our ability to derive actionable insights from PCAP data and supports more reliable analytics pipelines.
June 2025 monthly summary for carma-analytics-fotda: Delivered the PCAP Analysis Toolkit to enable faster PCAP data analysis and improved decoding visibility, driving faster troubleshooting and data quality assessment. This work enhances our ability to derive actionable insights from PCAP data and supports more reliable analytics pipelines.
May 2025 monthly summary for usdot-fhwa-stol/carma-analytics-fotda focusing on IHP2 data analysis tooling for ROS1 bag data and platooning metrics.
May 2025 monthly summary for usdot-fhwa-stol/carma-analytics-fotda focusing on IHP2 data analysis tooling for ROS1 bag data and platooning metrics.
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