With the passage of Pennsylvania Act 89 in 2013—a comprehensive piece of state transportation legislation that calls for an additional $2.4 billion funding over five years—PennDOT identified traffic signals as an area of necessary investment. PennDOT established the Green Light-Go (GLG) Program to manage the dedicated traffic signal funding and corresponding maintenance and operations projects. A byproduct of this program was implementation of TSAMS, developed by PennDOT, which Michael Baker led the data collection through coordination with the PennDOT Central Office and each of their eleven Engineering Districts.
We collected data from more than 8,600 traffic signals across Pennsylvania. During the course of one year our team collected nearly 20 million data fields for the TSAMS database for the 8,623 traffic signals analyzed. TSAMS was populated as a centralized database to support PennDOT’s future planning, design, maintenance and operational decision making.
To efficiently collect the necessary data, we employed our cutting-edge mobile LiDAR technology. Our LiDAR-equipped vans safely collected all visible assets to minimize traffic disruption and eliminated the need for “on-foot” technicians working in traffic lanes. Since all LiDAR data was collected at the intersections, PennDOT can also review data on other non-signal infrastructure assets at the intersections.
To maximize the asset management database, our data collection efforts were broken into three parts:
- Exposed Traffic Signal Infrastructure Assets: Mobile LiDAR-equipped vans were driven to map entire intersections collecting three-dimensional point clouds and corresponding spherical imagery using a Ladybug camera.
- Traffic Signal Cabinet Assets: A project-specific iPad mobile application was developed to efficiently and consistently collect inside the cabinet control equipment data. Field staff used iPads with the app to collect, store and transmit additional data to the database.
- Traffic Signal Records: Electronic files were transferred and attached to the database, and pertinent filed paper documents were scanned to electronically extract equipment information.