Skip to main content

Mobile LiDAR technology used to capture traffic signal data across Pennsylvania

Engineering, planning and consulting services company Michael Baker International recently completed a nearly US$7-million project for the Pennsylvania Department of Transportation (PennDOT) to collect data from more than 8,600 traffic signals across the state. Over a year, the Michael Baker team, working with PennDOT’s Traffic Signal Asset Management System (TSAMS), collected nearly 20 million data fields for each of the 8,623 traffic signals analysed, which populated a centralised database to support Pen
November 30, 2016 Read time: 2 mins
Engineering, planning and consulting services company Michael Baker International recently completed a nearly US$7-million project for the 6111 Pennsylvania Department of Transportation (PennDOT) to collect data from more than 8,600 traffic signals across the state.  Over a year, the Michael Baker team, working with PennDOT’s Traffic Signal Asset Management System (TSAMS), collected nearly 20 million data fields for each of the 8,623 traffic signals analysed, which populated a centralised database to support PennDOT’s future planning, design, maintenance and operational decision making.
 
With the passage of Pennsylvania Act 89 in 2013, PennDOT identified traffic signals as an area of necessary investment and established the Green Light-Go (GLG) program to manage the dedicated traffic signal funding and corresponding maintenance and operations projects

Michael Baker’s fleet of LiDAR-equipped vehicles are capable of surveying an area by measuring the distance to a target by illuminating it with two laser lights, each of which can measure up to 600,000 points per second with a total maximum measurement frequency of 1,200,000 points per second. The firm’s LiDAR equipped vans collected all visible assets to minimise traffic disruption and prevented technicians from working in traffic lanes.
 
Mobile LiDAR equipped vans collected data from exposed traffic signal infrastructure assets, mapping entire intersections in three-dimensional point clouds, while corresponding spherical imagery was collected using a ladybug camera.

Data from traffic signal cabinet assets was collected by field staff using a project-specific iPad mobile application (app). Electronic files of traffic signal records were transferred and attached to the database and pertinent filed paper documents were scanned to retrieve information electronically.

For more information on companies in this article

Related Content

  • Cloud computing technology benefits GIS
    July 17, 2012
    Geographic Information Systems are a relatively late adopter of cloud computing,but the benefits of host services for geospatial data and analysis are becoming clear. Jason Barnes reports Both the concept and the reality of cloud computing have been around for some time. More and more industry sectors are entrusting external service providers with the provision of their computing services via the internet. However, the Geographic Information System (GIS) industry has been slow to embrace the trend. This is
  • GeoSpock captures space and time to deliver database for IoT
    October 6, 2015
    According to Cambridge start-up GeoSpock, the use of geospatial data would improve driving and the scheduling of delivery van journeys would reduce congestion and accidents on high streets and cut fuel use. These are among the geospatial applications to be facilitated by a different type of database developed by the company, which uses knowledge of how the brain stores, manages and retrieves information to offer a database capable of supporting the growing Internet of Things (IoT).
  • Data goldmines offer rich pickings
    May 31, 2013
    Astronomical is not too grand a term to describe the current rate of growth in transportation-related data. Massive amounts of traffic related information, such as speed, volume, incidents and weather are being generated every second by road operators and users alike. Big data’ derives its name from the sheer amount and complexity of available raw data. Its potential value is starting to emerge among the intelligent transportation systems community. A gold rush is taking place to capture this value, with da
  • Simulating the effects of optimal mobility
    May 30, 2024
    Simulation-based optimisation is the foundation for real-time predictive analytics when it comes to optimal traffic signal programming, explain Sunny Chakravarty of Econolite and Lorenzo Meschini of PTV Group