Data Science and Analysis

Our data science team transforms complex data into actionable insights and intuitive tools, delivering the industry’s leading methods in safety and comfort analysis, network evaluation, and multimodal demand modeling. We not only analyze data, but also design custom analytical methodology and tools, interactive dashboards, and compelling visualizations that empower clients to explore data on their own and tell meaningful stories. By integrating GIS, statistical modeling, and modern programming tools, we help communities make confident, data-driven investment decisions that improve safety, expand mobility, and turn vision into reality.

What we do:

• Measure Comfort and Stress. We go beyond basic facility inventories to capture how networks feel for everyday users, and where targeted improvements could unlock low-stress mobility options. For example, learn about the Bicycle Comfort Index we developed for San Francisco.
• Analyze Access and Connectivity. We use advanced routing techniques that replicate how people actually travel, showing where investments in the transportation network would connect the most people to opportunity. Check out the Bicycle Network Analysis tool we developed for PeopleforBikes.
• Identify and Anticipate Safety Risks. We identify risks before crashes happen and target improvements that can save the most lives. For example, we co-developed the Safer Streets Priority Finder, a free, web-based tool that estimates segment-level crash risk and has supported over 1,500 safety studies to date.
• Model Trip Potential and Mode Shift. We help clients see where demand is — and where it could grow. Our models forecast walking and biking trips and reveal how networks and policies can shift everyday travel choices.
• Create Interactive Webmaps and Custom Tools. We put data in people’s hands. Our custom maps make analysis easy to explore and share, and the flexible tools we develop for clients make complex analysis easy and reproducible. See, for example, Tacoma’s crash data dashboard and the 14 distinct tools we developed as part of the ATX Walk Bike Roll project.

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Practice Lead:

 

Nan Jiang, Data Science Practice Lead