Models Coupling Urban Growth and Transportation Network Growth : An Algorithmic Systematic Review Approach

TL;DR

This paper presents an algorithmic systematic review method to analyze the scarcity of integrated quantitative models for urban and transportation network growth, highlighting disciplinary segmentation.

Contribution

It develops a formal iterative text-mining algorithm to retrieve relevant literature and assesses its convergence, addressing interdisciplinary communication gaps.

Findings

Discipline compartmentalization in urban and transportation modeling.

Algorithmic review confirms limited integration in existing models.

Sensitivity analysis of the retrieval algorithm.

Abstract

A broad bibliographical study suggests a scarcity of quantitative models of simulation integrating both network and urban growth. This absence may be due to diverging interests of concerned disciplines, resulting in a lack of communication. We propose to proceed to an algorithmic systematic review to give quantitative elements of answer to this question. A formal iterative algorithm to retrieve corpuses of references from initial keywords, based on text-mining, is developed and implemented. We study its convergence properties and do a sensitivity analysis. We then apply it on queries representative of the specific question, for which results tend to confirm the assumption of disciplines compartmentalisation.