Bicing Usage Prediction

This project focuses on predicting traffic speed using time-series forecasting techniques. By utilizing XGBoost, we aim to forecast future speeds based on historical sensor data. Accurate traffic speed predictions help in traffic management, route optimization, and smart city planning.

Smart Traffic Management with ML - Traffic volume prediction & accident risk assessment using XGBoost, LightGBM, MLflow & Docker

The project of the Artificial Intelligence Course

Google Maps–Inspired AI Traffic Route Guidance | Deep Learning + Heuristic Search | Real-World SCATS Data (Boroondara 2006)

Algorithm for approximating future green-time for a traffic signal. Based on SSD300 object recognition network.

Recipe Site Traffic Prediction: Utilising machine learning to forecast high traffic recipes on a recipe website. Improve user engagement and traffic with data-driven decisions.

This repository will contain my studies and codes for predicting traffic.

Course Project - ML Techniques

Graph Structure Learning for Traffic Prediction

ML-based traffic level predictor for Copenhagen rush hours. Includes a live, user-friendly website powered by GCP ML pipelines, CI/CD automation, and Terraform-based IaC.

Dijkstra adjacency distance matrices were calculated for 40 cities from traffic sensor locations provide by UTD19 https://utd19.ethz.ch/.

Here is a time series analysis using R and Arima models to predict air traffic for Hong Kong Airport.

Evaluation of incremental deep learning approach on real-time traffic prediction

A project about using VGRNN and TrajNet++ model to predict trajectory based on CFF16 dataset.

Pedestrians destination prediction

🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia

Traffic Flow Prediction in Urban Areas

Master Thesis at ETH Zurich, 2022.