Microsimulation parking choice and search model to assess dynamic pricing scenarios

Andrés Rodríguez, Rubén Cordera, Borja Alonso, Luigi dell'Olio and Juan Benavente

Transportation Research Part A: Policy and Practice, 2022, vol. 156, issue C, 253-269

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.

Keywords: Parking Choice; Parking Simulation Model; Stated Preference; Agent Based Simulation Model; Mixed Logit; Dynamic Parking Pricing Policies (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tra.2021.12.013

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