The goal of this project is to provide actionable data for government officials and advocates that promote bicycling and walking. Although the health and environmental benefits of a non-automobile commute are well known, it is still difficult to understand how to get more people to take up active transportation. Infrastructure can have a dramatic effect on cycling and waling adoption, but represents a significant outlay of government resources. Thus, concrete usage statistics are paramount for assessing and optimizing such spending. This project will create a vision-based cyclist and pedestrian counting system that will allow for automatic and human-assisted data collection and analysis. Unlike traditional non-vision counting methods, our system has the potential for much higher accuracy while providing valuable usage and demographic data that simply cannot be collected by other sensors.
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Name | Affiliation | Role | Position | |
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bpires@cmu.edu | Pires, Bernardo | Robotics Institute | PI | Faculty - Tenured |
Type | Name | Uploaded |
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Final Report | Automatic_Counting_of_Pedestrians.pdf | April 2, 2018, 5:15 a.m. |
Publication | Greensburg Vehicle and Pedestrian Study: South Main Street between West Otterman and Pittsburgh Street. | Dec. 2, 2020, 10:33 a.m. |
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