A reservation-based parking behavioral model for parking demand management in urban areas. (April 2023)

• Record Type: Journal Article
• Authors: Macea, Luis F.; Serrano, Iván; Carcache-Guas, Camila
• Is Part Of: Socio-economic planning sciences. Number 86(2023)
• Publication Date: 2023-04
• Subjects: Parking management -- Hybrid discrete choice model -- Parking reservation -- Parking policy -- Latent variables; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2022.101477
• Languages: English
• ISSNs: 0038-0121

Abstract

Abstract: The rapid increase in car ownership has become a land-use problem in many cities which have limited land for parking. It also has adverse impacts on congestion, air quality, energy consumption, as well as losses in productivity, among other consequences. The problem worsens in some cities due to the adoption of inefficient mandatory minimum parking policies for new projects, according to a building's use and size, which incentivizes driving. Therefore, it is necessary to assess appropriate parking management policies that maximize social welfare. In this regard, this paper presents a reservation-based parking behavioral hybrid choice model for parking demand management policies in urban areas, that appropriately represents the behavior of private vehicle users when choosing their parking site. The proposed model is statistically significant and consistent with expected behavior and microeconomic theory. The results demonstrate that the possibility of reserving a parking space has a significant impact on car parking market share on- and off-street. The three latent variables included in the model (pro-parking attitude, perception of risk for parking on- and off-street) have a significant effect on the modal split and the evaluation of appropriate parking policies that consider heterogeneity. The latent variable that most impacts the modal shift is the pro-parking attitude, which can generate up to 7% change in the modal partition. Highlights: The proposed model appropriately represents the behavior of private vehicle users when choosing their parking site. Three latent variables were identified as "pro-parking attitude" and "perception of risk for parking on- and off-street" . The possibility of reserving a parking space has a significant impact on car parking market share on- and off-street.