题名: |
Develop a Plan to Collect Pedestrian Infrastructure and Volume Data for Future Incorporation into Caltrans Accident Surveillance and Analysis System Database |
作者: |
Zhang, Y.; Proulx, F. R.; Ragland, D. R.; Schneider, R. J.; Grembek, O. |
关键词: |
Pedestrian accidents##Bicycle accidents##Infrastructure database##Volume data##Analysis system database##Data collection##TASAS system## |
摘要: |
This project evaluates the feasibility of developing a pedestrian and bicycle infrastructure database and volume database for the California state highway system. While Caltrans currently maintains such data for motor vehicles in the Traffic Accident Surveillance and Analysis System - Transportation System Network (TASAS-TSN) database, the agency does not keep records on pedestrian or bicycle facilities. This information is crucial for improving the safety of these vulnerable road users. This project developed a proposed database structure and corresponding data collection methodology. It is recommended that the databases be linked to TASAS using the connection ID instead of incorporating them directly into the existing database. The volume and infrastructure databases will be constructed separately to accommodate different data collection procedures. In particular, volume data should be updated more regularly than infrastructure data. Volume data must be collected during field visits either manually or using automated collection methods, while infrastructure data can be collected remotely using mapping services or in the field during field visits. The research team tested the structure and collection methodology by populating the database for 100 miles of state highway across two districts. Parallel to testing the consistency and integrity of the database, the team also generated a time-cost estimate for data collection for different facilities across the state highway system. The research team estimates that collecting the data in the field for the entire state highway system will require approximately 9,000 hours, while remote (computer-based) data collection will require about 4,000 hours. |
总页数: |
110 |
报告类型: |
科技报告 |