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Microsimulation parking choice and search model to assess dynamic pricing scenarios

Abstract: This article analyses the impact that different parking management policies may have on public roads. Policies were simulated using a new parking model based on two sub models: choice of parking place and search for parking place. The model considers curb traffic and was implemented into a traditional microsimulation traffic software. The parameters for the sub models were estimated from data collected in the city centre of Santander (Spain) and from a stated preferences survey asked to users of parking spaces. The model for testing policies was run on Aimsun simulation software creating a personalised API programmed using Python 3.7. The proposed model was able to dynamically simulate various policies based on charging for on-street parking spaces with fare updates at short time intervals of between 5 and 15 min. A sensitivity analysis was performed on different fare scenarios and considering different levels of information available to the users. As a result, this work demonstrates some benefits of dynamic fares such as reducing searching time, curb induced traffic and emissions as well as a new modal redistribution of parking choice between off-street and on-street supply. On the contrary, dynamic fares implied that users needed to spend a bit more time from their parking location to their destinations.

 Autoría: Rodríguez A., Cordera R., Alonso B., dell'Olio L., Benavente J.,

 Fuente: Transportation Research Part A : Policy and practice 2022, 156, 253-269

 Editorial: Elsevier Ltd

 Fecha de publicación: 01/02/2022

 Nº de páginas: 17

 Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.tra.2021.12.013

 ISSN: 0965-8564,1879-2375

 Proyecto español: TRA2017-85853-C2-1-R.

 Url de la publicación: https://doi.org/10.1016/j.tra.2021.12.013