LLMob is an intuitive framework that builds reasoning logic for LLMs in the context of personal activity trajectory generation.

Source code for superblockify

Platform where you can get help to learn how to ride a bike and improve your cycling, route recommendations, commute together in traffic, tips and much more.

The official implementation of the manuscript Learning the complexity of urban mobility with deep generative collaboration network.

Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks

📚 Projeto dedicado à identificação de gargalos, regiões críticas e padrões de acessibilidade na rede viária de Brasília por meio de métricas de grafos.

Prédicteur de congestion routière utilisant RandomForest sur données synthétiques. Classification multi-classes (faible/moyen/élevé) avec interface web.

An end-to-end Data Engineering and Machine Learning project that analyzes and forecasts urban mobility in Madrid. This project fuses real-time transit data (EMT API) with historical pedestrian traffic to train a suite of Prophet time-series models.

An open-source platform to unify global public transportation data and services.

Application of reinforcement learning to the management of traffic light intersection

Method for detecting and hierarchically organizing local centers and urban regions.

Agentes y Big Data aplicado a la optimización de recursos de movilidad urbana en la ciudad de Santander, España

SUMO

Urban data integration framework for mobility analysis

Projekt zrealizowałem w trakcie studiów w ramach publikacji "Communication management to improve the efficiency of intelligent transport systems" (https://www.mdpi.com/1996-1073/13/12/3087). Celem projektu było stworzenie oprogramowania do pomiaru czasów reakcji kierowców na podstawie nagrania ze skrzyżowania w Warszawie.

Real-time traffic object detection system using YOLOv3 and OpenCV’s DNN module. Detects vehicles, pedestrians, and road objects in live or recorded video streams, with FPS overlay and scene IoU analysis.

This repository contains implementations of advanced regression methods, including ordinary least squares, Poisson regression, and locally weighted regression. It also explores bias-variance decomposition for regularized mean estimators. The analysis is conducted on the Capital Bikesharing dataset using Python.

Data-driven Rider Satisfaction Score (RSS) for MBTA rapid transit combining operational metrics with passenger surveys. Interactive Streamlit dashboard with equity analysis.

Python simulation of the London Underground network that finds the fastest route between stations using weighted graph algorithms. Includes dynamic connections and optimization for travel time and network efficiency.

Descubra a Árvore Geradora Mínima (MST) das farmácias de Natal! 🗺️ Este repositório demonstra como Grafos e o Algoritmo de Kruskal podem ser usados para otimizar redes urbanas e o acesso a serviços de saúde. Inclui código Python e análise de resultados.