Mobile-Device Data, Non-Motorized Traffic Monitoring, and Estimation of Annual Average Daily Bicyclist and Pedestrian Flows

Summary:

Constructing and maintaining safe road networks for bicyclists, pedestrians and other nonmotorized road users require knowing the numbers and destinations of these users. Accurately estimating the volume of these users has been challenging because monitoring methods are limited compared to vehicle traffic counters. Data from mobile devices, however, offers a potential source of traveler routes. Researchers combined mobile data from existing platforms such as StreetLight and Strava with monitored bicyclist and pedestrian data to produce a data visualization tool that estimates bicyclist and pedestrian traffic within the Twin Cities metro area. Despite the inherent limitations of mobile data sources, such as inconsistent geographic coverage and demographic representation, MnDOT has begun using the visualization tool for approximations of bicyclist and pedestrian traffic in the Twin Cities area. Additional research is needed to improve the accuracy of the tool so estimates could support infrastructure decisions.

Final Deliverables:

• Report #2024-19
• Research Summary

Related Materials:

• Crowdsourcing meets transportation planning with bike and pedestrian data counts  - (News/Publication Article)
• The use of crowdsourced mobile data in estimating pedestrian and bicycle traffic: A systematic review  - (News/Publication Article)
• New Project: Mobile-Device Data, Non-Motorized Traffic Monitoring, and Estimation of Annual Average Daily Bicyclist and Pedestrian Flows  - (Blog Post)

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