Parking choice behavior of urban village residents considering parking risk: An integrated modeling approach

Abstract

With rising car ownership, the demand for parking and land for parking is increasing rapidly. This strains urban land resources and accentuates the performance of urban villages, characterized by limited space, high building density, narrow roadways, and few parking spaces, making parking challenging. To address this, the study focuses on guiding residents' parking choices from a parking management perspective, aiming to reduce the demand for parking spots among village members. In April 2021, a survey was conducted in Shenzhen City, where urban villages are widely dispersed. The survey revealed that residents primarily rely on on-street parking within the village, off-street parking within the village, and on-street parking outside the village. Due to the unquantifiable nature of the latent variable of parking risk and the impact of individual heterogeneity, this paper adopts a discrete selection model that integrates principal component analysis and mixed logit model (PCA-ML). The model demonstrated a good fit, indicating that parking charges, search time, and walking distance to home have negative impacts on parking choices. In addition, street parking outside the village is positively influenced by the parking risk attitude variable, while village parking remains unaffected. This study assists authoritative departments in understanding the factors that influence parking management in urban villages, thereafter, adopting targeted guidance to direct residents in urban villages to park their vehicles, mitigating the current situation of parking difficulties in urban villages. Furthermore, it contributes to achieve equitable and sustainable development of urban villages.