Latest Articles for Urban Planning

A new GNN method offers faster evaluation of traffic policies for cities.

Combining street-level and satellite imagery for better disaster response.

A new model improves traffic predictions following crashes for better management.

A new system enhances traffic monitoring and management in cities.

Studying how autonomous vehicles can improve traffic flow and reduce congestion.

Using smart technology to optimize traffic flow in growing cities.

This study presents a traffic flow model that accounts for connected and autonomous vehicles.

Climate change may increase West Nile Virus risk in the UK.

A project aims to improve fire department response time through data modeling.

Using data-driven methods to forecast sewer system behavior during heavy rain.

HAPNet combines hyperspectral and SAR data for better land cover classification.

Using dynamic graphs to reveal patterns in urban passenger travel.

A new dataset aims to improve traffic signal management using real images and diverse scenarios.

A look into unique connections between points in geometry using parabolic-taxicab distance.

City design affects how different groups meet and engage.

A new system enhances vehicle dispatching for ride-hailing services.

Learn how nonlocal conservation laws impact traffic and crowd dynamics.

CAPAs enhance wireless communication with better signal quality and coverage.

A model focuses on vehicle space to improve traffic management.

STGormer enhances traffic predictions by considering time and space.

A look into effective management of HOT lanes to reduce congestion.

A comprehensive look at understanding traffic patterns through complex data analysis.

DutyTTE improves travel time estimation by accounting for uncertainty in predictions.

A look at equity in urban transport access amid rising challenges.

New methods improve UAV signal mapping in complex urban settings.

A new model reveals how urban areas evolve through worker and company interactions.

Exploring the impact of self-supervised learning on geospatial data analysis.

A new framework improves traffic predictions by analyzing causal relationships and uncertainty.

A study on improving HOT lane efficiency and congestion management.

A new model enhances transportation demand forecasts by analyzing multiple urban features.

A new method enhances road traffic predictions by integrating regional knowledge.

A fresh approach to better predict human movements in urban areas.

A new framework enhances predictions by combining spatial and temporal data analysis.

Learn how to determine fair meeting spots using graph centers and centroids.

Examining public transit access for low-income riders in Greater Boston.

A framework for better predicting human movement using machine learning.

Comparing service times of cargo bikes and vans in urban delivery settings.

Poly2Vec simplifies the analysis of spatial relationships across various shapes.

ChatSUMO makes traffic simulation easier with natural language commands.

A new method enhances traffic forecasting accuracy through data decomposition and neural networks.