San Francisco Curb Space Parking Behavior Simulation in SUMO

A simulation study of parking behaviors around downtown San Francisco, developed by Miguel Jaller of UC Davis. The work includes a literature review on curb space management and data collection techniques. The data contains GIS information for three land-use sub-study areas (residential, commercial, mixed-use) and associated SUMO simulation scripts.

Use Cases

• Simulating parking search behavior based on the described parking scenarios.
• Evaluating curb space performance for different land uses (residential, commercial, mixed) based on the GIS study areas.
• Testing traffic micro-simulation models using the provided SUMO scripts.
• Analyzing the impact of off-street parking information availability on traffic patterns.

Strengths

• Includes GIS data for three distinct land-use study areas.
• Simulation scripts are provided for the open-source SUMO traffic simulator.
• Based on a case study of a specific geographic area (downtown San Francisco).

Limitations

• Row count and specific data file formats are unknown.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of California, Davis

Collection Method

Developed via a case study simulation using the SUMO traffic simulation software.

Geography

Downtown area of San Francisco, USA, with three sub-study areas.