Contextualizing Shared Autonomous Vehicle Parking

A Multi-Objective Land Use Planning Framework /.

As autonomous vehicles (AVs) transition from pilot projects to fully operational services, more context-based and nuanced solutions are required to assess their impact on land use planning for distinct development types, particularly in addressing longstanding parking challenges. However, most existing research remains high-level, focused on geographic boundaries rather than development types, or lacks contextual grounding. This limits the generalizability of findings for broader applications in transforming future land use planning practices at this critical juncture. This research addresses this gap by proposing a multi-objective land use planning framework that can be tailored to specific development types, integrating shared autonomous vehicles (SAVs) to tackle persistent parking challenges. The framework is then specifically applied to American suburban low-density residential developments, where suffer the most from existing parking regulations, while replacing minimum parking requirements (MPRs) is often impractical. Instead, SAVs serve as a critical instrument to make shared parking a viable solution for overcoming various challenges in such development types. The proposed model was tested through a real-world development in New Braunfels, TX. Results show that integrating SAVs can reduce total parking space requirements by 60% and reclaim up to 25% of total household space previously allocated to bundled parking. The spatial outputs of the model provide additional insights into SAV Parking Station (SAVPS) planning and design, offering context-specific and development-oriented perspectives on integrating SAVs into future land use planning.