
Anish Deva contributed to simulation and analytics enhancements across usdot-fhwa-stol/carma-config and carma-analytics-fotda, focusing on scalable map support and robust data analysis workflows. He delivered a comprehensive vector map for Town04, expanding simulation fidelity and enabling more realistic urban scenario modeling. In carma-analytics-fotda, Anish implemented Python-based speed analysis features, including error visualization and regression script refactoring, which improved maintainability and analytical depth. He also reduced production log noise in usdot-fhwa-OPS/V2X-Hub by refining logging levels in C++. His work demonstrated strong data engineering, code refactoring, and configuration management skills, resulting in more reliable, testable, and insightful software systems.

In April 2025, completed CARMA analytics enhancements for usdot-fhwa-stol/carma-analytics-fotda, delivering improvements focused on reliability, maintainability, and data-driven insights. Key improvements include unit-conversion constants, standardized saving of analysis results, percentile-based cross-track error threshold, and standard deviation visualization for speed-limit error plots; includes refactoring to streamline regression/analysis scripts and updates to thresholds. Re-enabled the full analytics workflow by removing commented-out code and import leftovers in guidance_scripts.py and related analysis scripts, restoring end-to-end analytical capability.
In April 2025, completed CARMA analytics enhancements for usdot-fhwa-stol/carma-analytics-fotda, delivering improvements focused on reliability, maintainability, and data-driven insights. Key improvements include unit-conversion constants, standardized saving of analysis results, percentile-based cross-track error threshold, and standard deviation visualization for speed-limit error plots; includes refactoring to streamline regression/analysis scripts and updates to thresholds. Re-enabled the full analytics workflow by removing commented-out code and import leftovers in guidance_scripts.py and related analysis scripts, restoring end-to-end analytical capability.
March 2025 performance snapshot: Delivered two high-impact features across V2X-Hub and CARMA Analytics Fotda, with notable improvements in production logging management and speed analytics capabilities. The work enhances observability, data-driven decision making, and safety/compliance insights while demonstrating cross-repo collaboration and software craftsmanship.
March 2025 performance snapshot: Delivered two high-impact features across V2X-Hub and CARMA Analytics Fotda, with notable improvements in production logging management and speed analytics capabilities. The work enhances observability, data-driven decision making, and safety/compliance insights while demonstrating cross-repo collaboration and software craftsmanship.
Monthly summary for 2024-12 focusing on carma-config feature delivery and its impact on simulation fidelity and testing coverage.
Monthly summary for 2024-12 focusing on carma-config feature delivery and its impact on simulation fidelity and testing coverage.
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