Microsimulation parking choice and search model to assess dynamic pricing scenarios

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.