Dynamic accessibility using Big Data: The role of the changing conditions of network congestion and destination attractiveness

TL;DR

This paper presents a dynamic approach to analyzing urban accessibility by considering real-time changes in network congestion and destination attractiveness, leveraging Big Data for more accurate insights.

Contribution

It introduces a novel dynamic methodology for urban accessibility analysis that accounts for fluctuating network and destination conditions using Big Data.

Findings

Enhanced understanding of temporal accessibility variations

Improved accuracy over static models

Potential for real-time urban planning applications

Abstract

This paper analyses urban accessibility using a fully dynamic approach.