Jan/Feb 2020 | V13 | Issue 76

The Pennsylvania Department of Transportation (PennDOT) saved an estimated $39 million in overall productivity through its mobile construction application program, part of its e-Construction implementation. PennDOT based its calculations on time saved using apps compared to older paper and manual processes. PennDOT’s goals include increasing field staff productivity, transforming labor-intensive paper processes through efficient mobile technology, and improving data collection and reporting capabilities. After implementing its first app in 2013, PennDOT now uses nine apps and has another two in development. The apps include mobile construction documents, punch lists, concrete inspection diaries, mileage and hour trackers, and payroll.

The Vermont Agency of Transportation (VTrans) is realizing benefits from its deployment of automated traffic signal performance measures (ATSPMs). VTrans can now monitor and count traffic in intersections with ATSPMs 24 hours a day, compared to past manual data collection every 1 to 2 years. This heightened monitoring allows the agency to get reports and deploy traffic signal staff proactively rather than react to calls from the public. In one case, VTrans received a complaint about a malfunctioning pedestrian light at an intersection 120 miles from headquarters. After installing ATSPMs, VTrans was able to review data and determine that the pedestrian push button was failing randomly, which was not evident during field observation.

As part of its safe transportation for every pedestrian (STEP) implementation, the District Department of Transportation (DDOT) in Washington, DC, deployed more than 580 leading pedestrian intervals (LPIs), which allow pedestrians to walk before vehicles get a green signal to turn. Under its Citywide Signal Optimization program, DDOT developed selection guidelines and criteria to evaluate intersections for LPI implementation. The guidelines capture the magnitude and severity of pedestrian-vehicle interactions at signalized intersections and identify locations with physical characteristics that make those interactions more dangerous. The data used to drive these decisions include crash data, pedestrian and vehicle volume counts, land use, and visual inspection of sight line obstructions and crosswalk locations.