Transportation Engineering & Intelligent Transportation Systems
Amir Reza Safari
AI & Computer VisionTraffic Researcher, Naples, Italy
I work on the traffic-state estimation, computer-vision, and digital-twin methods needed to understand how vehicles actually behave on motorways — from CCTV- and UAV-based vehicle detection, tracking, and re-identification to SUMO/TraCI simulation calibration and AI-based congestion monitoring and decision support.
Currently a Software Operator at CCAMON in Naples, following three years as a Digital Twin Research Fellow at Ce.S.M.A., University of Naples Federico II.
Research interests
Traffic state estimation & prediction
Data-driven and physics-informed approaches for estimating and predicting flow, density, and speed under sparse, noisy, or heterogeneous observations.
AI-based traffic monitoring & management
Intelligent methods for motorway and urban traffic monitoring, congestion analysis, and decision support.
Digital twins & traffic simulation
Integrating real-world traffic observations with simulation models such as SUMO/TraCI for calibration, validation, and management applications.
Computer vision for transportation data
Vehicle detection, tracking, re-identification, trajectory extraction, and lane-level speed estimation from CCTV, UAV, and multi-camera traffic video.
Highlights
Time to Closest Approach as a Feasibility Descriptor for Highway Merging
A geometric, sensor-derived alternative to self-reported gap acceptance, validated against CCTV and drone-tracked merges.
From Federico II to CCAMON
Three years as a Digital Twin Research Fellow at Ce.S.M.A., now a Software Operator at CCAMON, applying computer vision and traffic analysis to smart-road deployment across Italy.
Full background & CV →Best Master's Thesis Award, 2025–26
Premio Jacopetti-Tocchetti, Rotary Club Napoli and Distretto Rotary 2101 — plus a competitive CeSMA Research Scholarship for digital-twin research.
See honors & service →