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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Urban renewal projects worldwide focus mainly on resolving motorized, personal, and low occupancy problems instead of sustainable mobility. As part of the process, traditional field audits have a high cost in time and resources. This paper reviews a spatial model of accessibility and habitability of the streets, oriented to the location of the volume of people moving sustainably out of an extensive street network. The exercise site is in the Monterrey Metropolitan Area, the second largest in Mexico. Here, the population that moves sustainably as the collective (public and enterprise transportation) and the active (cycling, walking, and others) represents a considerable portion (49%) of travelers, thus, confirming the need for intervention. The spatial model is elaborated in a Geographical Information System (GIS), and the main results are compared with the actual public transport demand using a neural networks process. The results of the tool as a predictor have a 91% efficiency, making it possible to determine the location of urban renewal projects related to the volume of people moving sustainably.

Details

Title
Neural Network and Spatial Model to Estimate Sustainable Transport Demand in an Extensive Metropolitan Area
Author
Barreda-Luna, Antonio A 1   VIAFID ORCID Logo  ; Rodríguez-Reséndiz, Juvenal 1   VIAFID ORCID Logo  ; Alejandro Flores Rangel 2 ; Rodríguez-Abreo, Omar 2   VIAFID ORCID Logo 

 Facultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, Mexico; [email protected] 
 Industrial Technologies Division, Universidad Politécnica de Querétaro, Querétaro 76240, Mexico; [email protected]; Red de Investigación OAC Optimización, Automatización y Control. El Marques, Querétaro 76240, Mexico 
First page
4872
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2663114572
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.