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Microsimulation parking choice and search model to assess dynamic pricing scenarios
Highlights New micro-simulation combined parking choice and searching model. Dynamic pricing policies assessment. Introducing logit choice model considering informed and uninformed drivers. Applicability to scenario evaluation in areas with on-street and off-street parking. Simulations show that dynamic pricing scenarios performed better.
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.
Microsimulation parking choice and search model to assess dynamic pricing scenarios
Highlights New micro-simulation combined parking choice and searching model. Dynamic pricing policies assessment. Introducing logit choice model considering informed and uninformed drivers. Applicability to scenario evaluation in areas with on-street and off-street parking. Simulations show that dynamic pricing scenarios performed better.
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.
Microsimulation parking choice and search model to assess dynamic pricing scenarios
Rodríguez, Andrés (author) / Cordera, Rubén (author) / Alonso, Borja (author) / dell'Olio, Luigi (author) / Benavente, Juan (author)
Transportation Research Part A: Policy and Practice ; 156 ; 253-269
2022-01-01
17 pages
Article (Journal)
Electronic Resource
English
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