Mobilità Urbana Multimodale e Simulazione di Flotte EV
MobilitySimulator modella il movimento di milioni di veicoli autonomi, bus elettrici e pedoni nelle aree metropolitane. Accoppiando la fisica del traffico con le reti elettriche, ottimizza la pianificazione urbana.
Mobility Simulation Core Zonal Architecture
Central Controller: Mobility Simulation Core — Multi-Agent Urban Platform
Zonal Control Units & TSN Ring
- Agent-Based Trip Demand Generator
- Microscopic SUMO / MATSim Traffic Solver
- Electrical Distribution Grid Power Flow
- Dynamic Public Transit Optimizer
- Urban Policy & Geofencing Scenario Evaluator
Simulare i Duplici Impatti dell'Elettrificazione delle Flotte e dell'Autonomia sulle Città
Introdurre 10.000 robotaxi in una metropoli trasforma il traffico, i parcheggi e la rete elettrica. MobilitySimulator esegue simulazioni ad agenti su intere regioni metropolitane, modellando scelte di percorso, scarica della batteria e code di ricarica.
Core Engineering Areas
- Agent-Based Activity Simulation — Simulating individual commuter choices: home departure times, modal choices (car, transit, autonomous shuttle), and destination routing based on dynamic utility functions.
- Traffic and Power Grid Coupling — Connecting vehicle battery drain telemetry directly into electrical distribution substation load models to evaluate charging congestion.
- Autonomous Robotaxi Fleet Dispatch — Applying centralized and distributed matching algorithms to assign available autonomous vehicles to incoming ride requests with minimal wait times.
Technical Articles
Related Cluster Architecture Specifications
- AutomotiveSDV — Full SDV Stack & Reference Architecture
- A2HCard — Agent-to-Human (A2H) Interface Cards & In-Cabin Autonomous Interaction Manifests
- A2HumanCard — Standardized In-Vehicle AI Agent Capability Discovery, Trust & Authorization Cards
- AIDrivenSynBio — AI-Driven Synthetic Biology for Automotive In-Cabin Air Purification, Bio-Engineered Pathogen Scavengers & Molecular Biosensors