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Information about pedestrian infrastructure and volume is indispensable to monitoring, evaluating, and improving the environment for comfortable and safe walking. However, determining and organizing the various types of data in a way that is easy to update and analyze can present challenges. This study designed and developed a relational database for pedestrian infrastructure and volume and included two core components (node table and approach table) and several subcomponents (tables for crosswalks, sidewalks, buffers, signs, transits, bikeways, bicycle parking, and volumes). Important measurements were proposed on the basis of the literature and practice review and grouped into different component categories on the basis of their attributes and relationships. Links were defined according to their relative locations to connect all the components. An infrastructure data collection pilot was conducted across 100 mi (161 km) of California highways using computer imagery, and across 7 mi (11.27 km) of those highways by field inventory, to prove the feasibility of the database. Time costs associated with collecting infrastructure data for the entire state highway system were estimated to be 4,006 h and 8,935 h for using computer and field collection methods, respectively. This study demonstrated that the database was easy to maintain, flexible to update, and feasible for data collection both by computer imagery and in the field. Although most data in the database were related to pedestrians, basic bicyclist-related information was also included to demonstrate the transferability of the database to store bicyclist infrastructure and volume in the future.
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Stored only when both papers are in the corpus — 11 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.