Leveraging Activity Based Models to Enhance Sustainable Mobility

Contact: David Wasserman, Civic Analytics Leader, Alta

The historical application of travel demand models inform and facilitate the expansion of interstate highway systems. While these megaprojects enabled a new era of mobility, it also severed communities, with a wide range of impacts following it. The initial purpose of modeling has had a long shadow over its history, assumptions, and implicit values that can still be observed today, from failing to address induced demand to equity issues with community impacts.

As our methods have evolved to include large-scale observation from mobile trace data and activity based models, it’s possible and necessary to ask new questions. New challenges from climate change to the need for equitable access to opportunities need creative solutions. And the historical analytical frames models, while useful, are insufficient.

Replica helps organize the world’s information about the built environment and makes it accessible, valuable, and actionable. Alta has a history of partnering with the company to leverage their models to make informed, impactful decisions about the places that matter to the communities we work with.

Our latest partnership demonstrates ways collaboration can foster more sustainable and equitable communities through new modeling tools that help us plan for the future.

Mobility is directly connected to equity, from environmental justice to health and safety. Additionally, as we work with partners on an NCHRP Report on the Benefits of Gap Closure, research indicates that benefits ranging from health to emissions depend on how behavior changes (mode shift, new active trips). Beyond connections to tangible benefits of infrastructure investments, if people do not use multimodal transportation infrastructure, the political will for those investments will diminish, and the ability to challenge the status quo dies. Modeling is one tool to develop estimates and metrics that help us understand latent and existing demand for active travel.

Approaches: A Sustainable Transportation Toolbox

Alta uses a diversity of techniques to understand latent demand. One approach is evaluating active trip potential in communities where short vehicle trips that could be made by walking or biking are mapped and visualized. This serves as a compelling latent demand metric and helps illustrate the potential changes active transportation modes might bring to a community.

This enables us to target investments where latent demand for active travel is most likely. Further contextual analysis can help us understand which trips are targets for conversion. We have integrated Replica’s modeled outputs into multiple different types of analysis where we leverage travel, land use, and synthetic populations across a range of applications.

Examples of Alta’s applications of Replica data include:

• Live Work Play: Integrates short trip rates specific to each mode into a latent demand model alongside other demographic and land use data from EPA’s, SLD, OSM, and others.
• Context Sensitive Projections: We’ve also integrated Replica into our approaches for demand projections, including one we used as part of our economic benefit analysis with the Ecusta Trail in Brevard, NC.
• Multimodal Safety: Replica data adds context to our Vision Zero and related safety work, including collision profiles and informing improvements along a network.
• Enhanced Equity Analysis: Replica enables us to expand the impact of an equity analysis by looking at more than where underserved populations live, but where and how they travel to design specific projects addressing historical harms to communities.

Case Study: Traveler Alignment Analysis for Utah Department of Transportation (UDOT)

There is tremendous active trip potential across Utah, and infrastructure investments are key to unlocking it. Alta worked with UDOT and its Research and Innovation Division (UTRAC) to understand which bike facilities might have the highest impact on mode shift if built. The team provided a statewide dynamic map showing origin-destination (OD) flows to visually illustrate where active modes are common and where short vehicle trips indicate high active trip potential.

Taking it one step further, we aimed to figure out what this means for individual projects. We used OD data from Replica to evaluate parallelism and proximity in addition to trip distance. The process allows for batch processing of all proposed projects at once and produces a qualitative index showing higher and lower active mode shift potential. We were able to evaluate both on- and off-street facilities within the same process and avoid some common pitfalls of other mode shift estimates by being project specific, rather than aggregated to a general area, and less data intensive than testing individual projects in a full travel demand model. The analysis was implemented as an ArcGIS tool that we provided to UDOT along with the statewide Replica OD data. They now use this tool in their prioritization process for selecting projects for Transportation Investment Fund (TIF) Active funding.

Case Study: Microtransit Market Analysis for King County Metro

Alta worked on a broad project with King County Metro to evaluate their flexible transit services called Metro Flex. The service operates as a point-to-point on-demand service in fixed areas around the Seattle metro area. Alta developed a series of white papers with topics ranging from designing service areas to evaluating current ridership trends and usage.

King County Metro had recently conducted on-board surveys of riders using their microtransit services, including demographic data like race, income, age, disability status, and household vehicle availability. They also collected information about their current trips and what mode they would be using if not microtransit. We compared the demographics of on-demand riders to both fixed route riders and the general population within the service area to understand ways in which on-demand riders did or did not differ from these other populations. Based on the results of this survey analysis, we developed a trip weighting formula using Replica trip tables. These had parallel information at the trip level, so we could apply these weights to the entire trip table in King County.

Once we had applied the weights to each trip, we could aggregate to a geography to understand where concentrations of suitable trips are located. In this case, we aggregated to the census block group, shown on the map below. King County Metro could use an analysis like this to adjust existing service areas to capture high ridership potential areas, or even create new service areas. This analysis strategy can also be tailored to emphasize target populations the agency wants to prioritize serving. For example, if the County wanted to prioritize serving trips made by members of low income households, they can adjust the trip weights for that demographic variable.

What’s Next for Alta and Replica

Alta is paying attention to thermal comfort in design as demonstrated by our work on the LA River Trail, and there is more we can do to combine climate data with travel behavior. The data and tools needed for more equitable and climate aware transportation planning are available today. While the scale of these types of insights is new, many of the methods behind them are innovative examples of best practices in activity based modeling. We will continue to work with stakeholders to make this data relevant, while understanding its limitations in practice. Alta looks forward to working with data partners such as Heavy.AI and Replica on potential joint projects in the near future.

Learn more about Alta’s Civic Analytics practice here, and follow along for regular Alta updates.