StreetLight multimodal resource library


Why I Hope Big Data Can Help Stop Cycling Fatalities

With cycling fatalities on the rise, bike riding doesn’t feel very safe right now. These are the ways I hope Big Data can help planners make a safer future.

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Bike and Pedestrian Analytics

Proprietary machine learning differentiates bikes and pedestrians from vehicular traffic. Identify where active transportation happens most and measure the impact of your decisions.

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Virginia Bike Tourism: Measuring Economic Impact

Planners knew that tourists visited the Virginia Capital Trail, but they didn’t have metrics for measuring bicycle tourism’s economic impact. They turned to Big Data for detailed information about bike and pedestrian trips.

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Multimodal Planning in the City of Toronto

Analytics informed planning studies for “Gateway Mobility Hubs” that will provide convenient, affordable, multimodal modes and improve connections to transit options in Toronto’s outskirts.

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Active Transportation Metrics: Methodology and Validation

A brief summary of StreetLight’s active transportation metrics, methodology, and validation.

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