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Shared autonomous vehicles (SAVs) are a major development direction in international scientific and technological innovation. One of the most popular features of SAVs in the urban space is that they can significantly reduce the need for parking. The urban underground parking space (UPS) is currently the largest static traffic space, especially in high-density urban centers. Under the SAV scenario, the need for the renewal of UPS will increase in the near future. However, renewal of the UPS is difficult due to its special form features, which are greatly restricted by the external environment, thus necessitating targeted methods and strategies. This research first conducted field investigations and data collection on the spatial morphology and service conditions of typical UPSs in different areas of Hangzhou city. Based on the driver status response and the multi-objective attribute models, the time-series evaluation method and function replacement decision model for the sustainable renewal of underground parking were established. The research also discusses appropriate design strategies for the combination of spatial characteristics and functional replacement goals of typical samples. The conclusions will provide scientific guidance for the future design practice of architects and urban designers in SAV.

Sustainable Renewal of Underground Parking Space in the Scenario of Shared Autonomous Vehicles