StreetLight Data adds ability to measure bike, pedestrian, and vehicular traffic

San Francisco — StreetLight Data, Inc., a provider of big data analytics for mobility, debuted an industry-first with the capability to measure bicycle and pedestrian traffic, virtually anywhere, in addition to vehicular traffic. The addition of bike and pedestrian analytics to StreetLight InSight is the first new product introduction coming out of its Multimodal Measurement Initiative (M²Initiative), an industry working group established to collaborate on the issue of multimodal travel interactions. A comprehensive set of bike and pedestrian features is now available as part of the Multi Mode subscription to StreetLight InSight, the company’s core SaaS platform.

StreetLight Data has developed complex proprietary machine learning to differentiate bikes and pedestrians from vehicular traffic, creating a digital dashboard of bicycle and pedestrian activity on roads, bike lanes, sidewalks, even parks. StreetLight InSight Multi Mode allows transportation professionals to analyze and visualize bicycle and pedestrian transportation in any neighborhood, or on any road in just a few clicks. Professionals can leverage the new metrics to target where investments can boost “active transportation” and measure the impact of decisions right from their desktop.

“StreetLight Data has long led the industry with in-depth analytics that describe the mobility patterns of vehicle traffic,” said StreetLight Data CEO Laura Schewel. “It is critical to develop a granular analysis of bike and pedestrian traffic to better see a complete picture of today’s complex mobility landscape. Our industry has been in the dark for years on bike and pedestrian movement because of the cost and difficulty of data collection. Now we can shed light on these mobility trends, giving planners the ability to make smart decisions about policy and infrastructure investment.”

This new functionality enables transportation planners and local, state and national transportation agencies to perform a deep analysis and determine key factors such as: Which days and roads have the highest biking volume? What time of day? What are common origins-destinations of trips? What is the trip purpose? And many more questions.

Schewel added, “My hope is that by being able to measure bikes and pedestrians, we can manage towards a future where these modes of travel are more prevalent.”