Then + Now is a blog series on the evolution of the transportation planning practice. This series sprung out of our 50th anniversary theme “Honoring the past > Shaping the future.” Last year, we looked back on our rich history of innovation, and now, we’ll dive into specific areas of transportation to tell the story of how it has changed over the years. In each installment of the series, our experts cover a specific topic – such as resilience, modeling, or transit network planning – recounting the work that propelled it forward and sharing key considerations as we plan for the future.
Planners call it scenario planning; modelers call it risk analysis. However you define it, preparing for the future is a risky endeavor full of uncertainties. With the increased number and magnitude of disruptions – such as new and emerging technologies and public health concerns (like the COVID-19 pandemic) – uncertainty is more salient than ever. Many things we once held as constants, or as deeply held beliefs in transportation, are being challenged. As a result, the traditional data sources and techniques we once relied on to predict the future often fall short. It makes our job as transportation practitioners much more difficult, as we are often faced with the question “what if?”
The good news is we don’t have to reinvent the wheel or completely toss the approaches that have worked for us in the past. We only need to improve upon them. Preparing for the future is a practice that continues to evolve, and we are excited about new tools and methods that can robustly help agencies address uncertainty to make better decisions. To understand where this practice is moving, let’s look back at traditional methods of preparing for the future and identify how they can be improved.
Then: Scenario Planning and Risk Assessments
Qualitative scenario planning is a process that considers how trends and drivers of change (e.g., urbanization, technology, globalization) will impact a community and its transportation systems. The process involves leveraging resources such as insights from local experts, questionnaires, surveys, and public engagement initiatives. Through storytelling, collaboration, and discussion, we then develop a few plausible future scenarios to help agencies design strategies and policies that hedge against a handful of futures.
Travel demand models and analytical tools take a quantitative approach. They provide more clarity around the potential impacts and effects of different scenarios. These methods use detailed quantitative assumptions as inputs that may include land use, demographics, technology adoption rates, pace of climate change, or comfort with sharing rides. We use models to assess how these trends could change when, where, and how people travel.
Both qualitative scenario planning and travel demand models share similar challenges:
Reliability: We can produce reliable predictions when our methods are validated against actual events, experiences, or expertise. However, with rapid change, the assumptions about human behavior and travel choices are less reliable.
Feasibility: To test a range of different input assumptions, hundreds (or even thousands!) of scenarios would need to be developed – something that is not feasible with either of these methods.
Read this blog post to dig deeper into the benefits and drawbacks of these methods.
So, what are practitioners doing to improve and build on these traditional methods?
Now: A Range of Futures
When California sought to understand high speed rail ridership, it embarked on the first mega-project to apply the concept of a rigorous risk analysis to evaluate a range of futures. To do this, we helped them evolve from a traditional scenario planning process of running a few alternative scenarios (representing alternative futures) to an innovative process that modeled thousands of futures. Ridership and revenue forecasts for a “range of futures” accounted for the uncertainty of key assumptions that could affect future travel behavior that was in turn reflected in different values of key model inputs. This allowed California to quantify the probability of meeting ridership and revenue thresholds.
The types of uncertainties that were evaluated included different population and employment growth assumptions, the level of service offered by the proposed system and competing modes, the attractiveness of high-speed rail, the propensity to make long-distance trips, and the market penetration of future technologies. The risk analysis supported various stages of this mega project effort, including the analysis of alternative alignments and station locations, environmental documents, benefit-cost analysis, and business planning.
Looking To the Future: Exploratory Modeling and Analysis
The “range of futures” approach to scenario planning laid the foundation for our development of the FHWA Travel Model Improvement Exploratory Modeling and Analysis Tool (TMIP-EMAT or EMAT). EMAT is a set of open-source exploratory modeling and analysis tools that can study thousands of scenarios in a fraction of the time it takes a traditional model to run. By running thousands of scenarios relatively quickly, EMAT can help you explore the interactions among variables to better understand the relationship between policy decisions, projects, build scenarios, and performance metrics. But, what does this mean for you as a transportation practitioner?
Three things you need to know about EMAT and how it will impact your approach to scenario planning:
EMAT doesn’t aim to replace your agency’s rigorously calibrated and validated travel demand and simulation models. The super-powered model of the future is the one you already have. EMAT simply expands the power of a model by acting as a wrapper around it, allowing it to produce thousands of “futures” in weeks (versus months or years) by systematically varying the model inputs and variables across the full range of their possible values.
Making EMAT’s outputs accessible to everyday transportation practitioners is key to maximizing its analytical power. We developed Tandem, a web-based dashboard that allows users to visualize and interact with a wide range of possible futures generated by EMAT. Tandem offers various automated procedures and visualization features that are shown below. These help you maximize the value for your given budget by decreasing the labor hours and resources required by an analyst to set up, run, and summarize model outputs. Try the EMAT + Tandem demo dashboard here.
EMAT can revolutionize your decision-making. You can assess how the interactions between the policy levers and uncertainty factors affect performance. Its algorithms and optimization features allow you to evaluate which combinations of individual policy levers are most successful in helping you reach your objectives under various conditions.
Agencies like Denver Department of Transportation and Infrastructure (DOTI) are already taking advantage of EMAT + Tandem for long-range planning work.
Equipped with EMAT results and stakeholder feedback, DOTI was able to develop objectives that support achieving a desired future in Denver. Using the dashboard, DOTI identified which policies will support movement towards a specific outcome or target and which potential uncertainties could deter that progress. This analysis provided them with information about the policy levers that are most impactful for their goals and what they might need to mitigate in the future.
You can use EMAT + Tandem to assess strategies like:
Highway capacity expansion
Managed Lanes and/or toll policies, including CAV lanes
Transit frequency, fare, or travel time improvements
Travel demand management policies such as encouraging telecommuting, increasing parking costs, etc.
Transit Oriented Development or other land-use policies
Want to understand how it works or get started? Dive into the inner workings of EMAT here and contact our experts today!
Rachel Copperman, PhD
Model Development National Practice Lead and Austin, Texas Office Director