Eclipse MOSAIC is a Multi-Domain and Multi-Scale Simulation Framework for Automated and Connected Mobility Scenarios.
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Updated
Apr 16, 2026 - Java
Eclipse MOSAIC is a Multi-Domain and Multi-Scale Simulation Framework for Automated and Connected Mobility Scenarios.
Berlin Sumo Traffic (BeST) Scenario
Data from 267 bike sharing schemes across Europe - 43 million km & 88000 bikes
mobinha is a self driving system implementation project of INHA university.
Service that matches signal lane geometries to bike routes (IEEE ISC2 2022, ACM SIGSPATIAL 2023)
A comprehensive ride-pooling simulation engine featuring VRP optimization (OR-Tools), dynamic pricing algorithms and ML-based demand prediction.
Next-Generation Intelligent Decision Support System (IDSS) for Indian Railways. A "Co-Pilot" for controllers that uses a Hybrid Intelligence Architecture (Reinforcement Learning + Operations Research) to optimize train scheduling, minimize delays, and ensure safety via Explainable AI. 🚂🤖🇮🇳
This repository contains the 3D models developed for better visualization of a smart mobility system Hyperloop, first publicly mentioned the Hyperloop by Elon Musk in 2012.
An AI-driven Smart Mobility solution for India, providing EV trip planning, on-route charging stops, and CO2 emission savings calculations.
Smart mobility web app that recommends safer urban routes using real-time signals, AI safety scoring, and explainable insights.
DeepTrafficQ is a reinforcement learning-based traffic signal control system that uses Deep Q-Networks (DQN) to minimize vehicle waiting times at a 4-way intersection. By leveraging Q-learning with experience replay and a convolutional neural network (CNN), the agent dynamically adjusts traffic light phases to optimize traffic flow.
AI-powered EV charging platform with nearest station finder, CO₂ comparison, smart route planning, and AI-based EV infrastructure location analysis using Map and Weather APIs.
SynapticGrid is an AI-driven system designed to make cities more efficient, sustainable, and livable by optimizing smart energy grids, waste management, and traffic flow through IoT sensors, real-time data processing, and reinforcement learning algorithms. The modular platform continuously learns and improves, helping urban environments
Welcome to Lab-42 - Open-Techlab for Makers 🤖🛠️
I'm an urban technologist and planner, trained at the **Massachusetts Institute of Technology (MIT)** with a focus on sustainable mobility and city innovation. My work blends engineering, design, data, and policy to create impactful urban solutions.
🚄 Simulate and analyze Roboflow AI metrics for enhanced performance testing and optimization in train systems through a comprehensive digital twin environment.
Backend API for the Smart Mobility Bike Accident Detection system (Thingy:91).
ITE@UIUC Data Science Team EOH 2024 Data Visualization
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