Abstract
Discussions on how urban space would be transformed by the use of autonomous vehicles (AVs) are scarce. This study identifies the impacts caused by the shared use of AVs on urban parking and urban space management. An estimation method was formulated considering the reduction in parking demand, the possible alteration in vehicle ownership, and the reallocation of urban space. A case study was performed in a 673,220 m2 area through scenarios created by using real data of parking spaces and the results of previous studies. Results showed that parking spaces can be saved with the use of shared AVs, which would allow the reallocation of urban space to new uses (for example, implementation of around 12,000 bike-sharing docking spots, 10 km bike lanes, 7 km additional traffic lane or 140 ‘parklets’). The results contribute to revealing the positive impacts of AVs.
Highlights
As autonomous vehicles (AVs) are under development, analysis of their impacts has become important for understanding how they would affect people and space management
A method was developed to estimate the reduction in demand for parking according to alteration in ownership and the shared use of autonomous vehicles (SAV), as well as to estimate the new uses of the urban space saved according to the priorities of decision makers
The modal share, the type of ownership and parking could cause a significant alteration in public parking space management, which could be transformed into new uses according to the priorities of decision makers
Summary
As autonomous vehicles (AVs) are under development, analysis of their impacts has become important for understanding how they would affect people and space management. Existing studies [9,14,19,20,21,22] focused on formulating models and calculating the reduction in the number of vehicles and parking spaces. This research focuses on the transformation in urban space generated by the use of AVs considering how changes in number, location and use of parking spaces could save urban space and which new functions could be given to them. A method was developed to estimate the reduction in demand for parking according to alteration in ownership and the shared use of autonomous vehicles (SAV), as well as to estimate the new uses of the urban space saved according to the priorities of decision makers. Different scenarios were created based on previous studies and real data of parking spaces were applied
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