A Blueprint for Applying Big Data to Small Projects
Corresponding Author: Laura Schewel, StreetLight Data
Presented By: Laura Schewel, StreetLight Data, Inc.
Historically, one of the transportation industry’s greatest planning challenges has been the lack of information about communities’ travel patterns at a local scale. When planners lack the budgets required for intensive planning studies, big data often proves to be a valuable, cost-effective strategy for obtaining critical mobility insights. In this session, Laura Schewel will demonstrate how to glean actionable transportation planning insights from big data, and explore how big data can empower planners by simplifying data collection.
This session will provide planners with a pragmatic guide for gathering and deploying big data insights through two unique Virginia case studies: a transportation demand project in Northern Virginia, and a regional travel pattern analysis project in Fredericksburg. Northern Virginia is one of the most congested regions in the U.S., but dense suburban development precludes expanding the community’s crowded highways. With big data, planners were able to diagnose some barriers to accessing destinations, identify multimodal solutions and then present them to community stakeholders to gather feedback. When new express ways on the I-95 corridor created congestion problems in Fredericksburg, the community looked to GPS data to understand the real-world travel patterns to, from and within the GWRC region. This information is being used to identify, screen, and evaluate non-pavement approaches to reducing congestion and improving mobility in the region.
Based on her experience with key public and private sector project leaders involved in these projects, Laura will detail how stakeholders collaborated to transform archival data from mobile devices into useful metrics, used those metrics to diagnose transportation challenges, and finally evaluated and planned solution-oriented projects with community engagement and support. In both cases, using big data helped planners identify the communities that would benefit the most from multimodal initiatives as well as the specific infrastructure, transit, and policy changes that would yield the greatest benefits, in light of new knowledge about travel patterns. This approach allowed them to spend less time on data collection, and more time planning the initiatives that would truly improve communities’ access to destinations.
*Note: If selected, Laura will request participation from other stakeholders in these projects.