The City of Pittsburgh set out to make the city’s 1,300 miles of core city streets safer for pedestrians and bicyclists. To identify vulnerable corridors and neighborhoods, the City of Pittsburgh’s Department of Mobility and Infrastructure (DOMI) wanted to pinpoint where traffic related crashes were occurring. Although the team had existing vehicle data, they lacked bicycle and pedestrian travel data.
Analysts used bike and ped transportation analytics overlaid with crash data to help identify the areas most needing safety improvements.
In the case study, you’ll learn how they:
Overlay bicycle and pedestrian high-travel corridors with actual crash data
Create bicycle miles traveled (BMT) and pedestrian miles traveled (PMT) metrics
Discover that high-travel corridors do not necessarily correlate with crash severity
Get valuable urban safety insights from this detailed real-world analysis so that you and your team can build a safer city.
Download the Case Study
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“We no longer have to make assumptions in people’s trip activity and travel behaviors. Now we have data to support our research and it separates fact from fiction.”
City of Pittsburgh
Your biggest transportation challenges require better analytics
Origin-Destination for multiple modes
Granular, on-demand Metrics segmented by time of day and day of week