OPTIDENS: An optimization model to explore the conditions of possibility of slow but accessible urban areas - Archive ouverte HAL Access content directly
Journal Articles Environment and Planning B: Urban Analytics and City Science Year : 2020

OPTIDENS: An optimization model to explore the conditions of possibility of slow but accessible urban areas

Abstract

High levels of accessibility for people and jobs are the very essence of urban areas, as they allow agglomeration economies and also provide social benefits. In the past, slow modes of transportation meant population and activity densities were the only way to attain high accessibility levels. More recently, the high speed provided by cars has enabled people to choose their home and job locations within larger areas, while keeping high accessibility levels and their daily transport time budget constant. Consequently, this change in the nature of accessibility has led to urban sprawl and automobile dependency, and in turn to environmental and social issues. To tackle these issues, an optimized model called OPTIDENS has been developed in order to explore how we might obtain slow but accessible urban areas. OPTIDENS reallocates populations and jobs in order to meet contradictory expectations regarding urban forms and accessibility while minimizing car speed, the latter being a strategic goal in order to overcome automobile dependency. The model was tested in a mixed urban-rural area in France and points out the relative impacts of the different expectations on urban forms and on the required speeds.
Fichier principal
Vignette du fichier
optidens-evp (1).pdf (7.91 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02543806 , version 1 (18-01-2022)

Identifiers

Cite

Cyrille Genre-Grandpierre, Alena Melnikava, Serigne Gueye, Philippe Michelon. OPTIDENS: An optimization model to explore the conditions of possibility of slow but accessible urban areas. Environment and Planning B: Urban Analytics and City Science, 2020, 48, pp.239980832091303. ⟨10.1177/2399808320913034⟩. ⟨hal-02543806⟩
87 View
38 Download

Altmetric

Share

Gmail Facebook X LinkedIn More