2025 Modeling Mobility Conference Presentations

The Modeling Mobility Conference (September 14-17, 2025), hosted by Zephyr and the University of Minnesota Center for Transportation Studies, is the premier forum for professionals working with travel models, transportation data, and quantitative analysis. As gold sponsors, we're excited to have the opportunity to help build a community committed to learning, sharing, and advancing the field of travel analysis. Visit us at booth #1 or check out our presentations and sessions below.

Sunday, September 14

Model Calibration: Panel

We still frequently rely on travel models which are several years out of date to inform planning decisions. This panel will explore the latest perspectives on travel demand model calibration, drawing from both current and emerging practices. We will address key questions like: How often are we re-calibrating our models? Which data sources are we leveraging? How much time and effort are required for this process? Are there relevant emerging technologies? How would we use more frequently updated travel models in our planning process? Ultimately, this panel aims to identify actionable next steps to help keep our travel demand models current and effective.

• 1:30 – 3:00 PM

• Johnson Great Room

Exploring Post-Pandemic Travel Modeling: Panel

Telework Assumptions and Uncertainties of Transit Ridership Forecasting

The impacts of the pandemic and its induced changes to telework have been extensively documented in the literature. Travel demand modelers and forecasters are now more conscious of the telework assumptions used in the travel demand models and have introduced ways to account for the potential effects of various telework assumptions on travel demand and ridership forecasting. In this study, we summarized our recent findings related to the uncertainties of transit ridership forecasting stemming from telework assumptions.

• 3:30 – 5:00 PM

• Ski-U-Mah

Monday, September 15

Data / Survey: Listen & Engage

Understanding Shifts in Household Travel: A Comparative Analysis of Surveys from the Houston Region

Household travel surveys (HTS) serve as a vital tool for enhancing travel demand models, forecasting future traffic volumes, assessing regional transportation plans, and understanding evolving travel behaviors, particularly as societal, economic, and technological factors shape mobility patterns over time. We analyzed data from the Texas Department of Transportation’s (TXDOT) 2023–2024 HTS and the agency’s previous survey conducted in 2007–2009. This longitudinal assessment offers insights into how travel behaviors have shifted over the past 15+ years, highlighting the influence of major external factors, including the COVID-19 pandemic, advancements in transportation technology, and changing consumer behaviors.

• 8:30 – 10:00 AM

• Johnson Great Room

Modeling—Big Data Integration

Network-Based Travel Demand Model Using GPS Data: Herkimer-Oneida Counties Transportation Council Planning and Environmental Linkages Study

The Herkimer-Oneida Counties Transportation Council (HOCTC), is conducting a Planning and Environment Linkages (PEL) Study of the I-90 Exit 31 interchange in Utica, NY. Exit 31 is a key regional interchange serving diverse land uses that faces safety and efficiency challenges. This presentation introduces a prototype travel demand model (TDM) tool developed to analyze existing and future network operations for small Metropolitan Planning Organizations (MPOs). These agencies often do not have forecasting tools, which are cost prohibitive to develop and maintain. The presentation showcases how GPS data derived from TomTom, a big data vendor, was used to develop a model to forecast highway demand.

• 8:30 – 10:00 AM

• Thomas H. Swain Room

Mesoscopic and Microscopic Simulation: What is the Value of Dynamic Traffic Assignment?

Isolating the Effects of High-Occupancy Vehicle Weaving: A Trajectory-Based Microsimulation Approach

High-occupancy vehicle (HOV) lane weaving is often recognized as a significant contributor to freeway congestion, yet its isolated impact is rarely quantified due to confounding factors such as spillback from downstream bottlenecks, insufficient capacity at exit ramps, and other operational issues. To support an action plan by Caltrans to address degraded HOV lanes, this study systematically evaluates whether weaving maneuvers to and from continuous-access HOV lanes are primary causes of performance degradation on freeway segments. Advanced microsimulation techniques were utilized to quantify these impacts comprehensively.

• 10:30 AM – 12:00 PM

• Ski-U-Mah

Scenario Planning for Sustainability

Assessing Network Connectivity, Vulnerability, and Resilience: A Case Study from Southern California

Natural disasters can force large, vulnerable populations to evacuate, placing tremendous pressure on the transportation network. This highlights the need for resilience studies that identify connectivity vulnerabilities and assess improvement projects aimed at ensuring timely evacuations and emergency responses. For San Bernardino and Western Riverside Counties, we are utilizing an expanded version of the San Bernardino Transportation Analysis Model (SBTAM) to support an emergency evacuation and network resiliency (EENR) study.

• 10:30 AM – 12:00 PM

• Johnson Great Room

Land Use and Transportation: Handle With Care

Evaluating Small Area Forecasting in a Rapidly Changing Landscape: A Review of Southern California Association of Government’s Small Area Secondary Variables Allocation Model Tool

The Southern California Association of Governments (SCAG) employs the Small Area Secondary Variables Allocation Model, or SASVAM, to disaggregate population and household data into secondary demographic variables, which support a wide range of planning applications, including travel demand modeling, long-range transportation planning, air quality analysis, and project evaluations. SASVAM primarily generates inputs for the population synthesizer (PopSyn), which feeds SCAG’s Travel Demand Model. This study conducted by a team led by Cambridge Systematics assessed the effectiveness of SASVAM and provided implementable recommendations to enhance forecasting accuracy.

• 1:30 – 3:00 PM

• Thomas H. Swain Room

Metrics and Planning

Illinois Emission Rankings for the Data Driven Decisions Tool

This presentation describes an analytical framework developed and implemented to evaluate and rank capacity expansion projects for inclusion in the Illinois Department of Transportation Data-Driven Decisions tool.

• 3:30 – 5:00 PM

• Johnson Great Room

Tuesday, September 16

Modeling Improvements

This session highlights recent innovations that strengthen the foundation and application of travel demand modeling. Topics include bridging Census geographies with Traffic Analysis Zones, evaluating reproducibility in transportation research, and examining the evolution of travel behavior in the Phoenix region from 2008–2024 to inform model calibration. Practical tools such as a streamlined project traffic dashboard in Excel and a utility platform designed to enhance model accessibility and efficiency will also be showcased.

• 10:30 AM – 12:00 PM

• Thomas H. Swain Room

Survey Methods

Advancing Household Travel Surveys: Innovations in Survey Instruments, Recruitment, and Big Data Integration

Household travel surveys remain a critical tool for understanding travel behavior and informing transportation planning. However, evolving technologies, shifting mobility patterns, and recruitment challenges necessitate continuous adaptation. This study, conducted by CS for the Delaware Valley Regional Planning Commission (DVRPC), synthesizes insights from recent HTS efforts across the United States, drawing from survey documentation and interviews with MPOs representing diverse methodological approaches and regional characteristics.

• 1:30 – 3:00 PM

• Thomas H. Swain Room
  

Transit Modeling

Colorado Mountain Rail Ridership Forecasts

The Colorado General Assembly directed the Colorado Department of Transportation (CDOT) to study alternatives for the Mountain Passenger Rail service in a corridor stretching 200 miles west from Denver to the city of Craig.  Major attractions along the corridor include two of the largest ski resorts in the state, Winter Park and Steamboat Springs. For this presentation, we will show how big data was used to develop an understanding of potential station catchment areas and, in turn, demand along the project corridor. We will demonstrate how a baseline mode share was established using available data, present on the modeling approach, and finally show forecasts developed for three scenarios.

• 1:30 – 3:00 PM

• Ski-U-Mah

Wednesday, September 17

Strategies for Multimodal Mobility

This session explores innovative modeling approaches to better evaluate and plan for emerging mobility, on-demand transit, and active transportation. Presenters will share applications from across the U.S., including enhancements to traditional travel models to account for biking comfort and safety, and demand estimation tools for trail gaps and e-mobility. A scalable framework for assessing on-demand transit’s impact on ridership will be presented alongside strategies to model micromobility and electric vehicle adoption using ActivitySim. Collectively, these efforts aim to equip planners with more responsive, data-driven tools to support multimodal investment decisions.

• 8:30 – 10:00 AM

• Ski-U-Mah

Artificial Intelligence Tools for Travel Analytics Programming Tasks Workshop

This interactive workshop will help participants learn how artificial intelligence (AI) can be applied to common travel analytics coding tasks. In addition to a hands-on demonstration of GitHub Codespaces + Copilot for data cleaning, model summarization, and documentation topics, you'll also learn how to build AI agents. Participants will walk away with a one page write-up with the findings from the session about best practices on artificial intelligence coding in travel analytics.

• 8:30 – 10:00 AM

• Johnson Great Room 

Freight and E-commerce: Listen & Engage

Meeting the Analytical Challenges of the E-Commerce Era: SANDAG Commercial Vehicle Model Update

Over the past decade, the explosive growth of e-commerce has produced a greater presence of commercial pickup and delivery activities in more places, posing challenges to commercial vehicle analytics and forecasting. In this presentation, we will discuss how the San Diego Association of Governments (SANDAG) updated their modeling tool to better reflect the realities of the e-commerce era, all within the larger context of needing forecasts for long-range planning and emissions analysis.

Improving the Modeling of Localized Commercial Vehicle Movements with GPS-Based Data

While many past truck models have depended on limited survey data from a few metropolitan areas around the country to model localized movements, new robust data sources have become available which have dramatically enhanced our understanding of commercial vehicle behavior. For the New York Metropolitan Transportation Authority (NYMTC), we harnessed LOCUS Truck expanded GPS-based origin-destination data to estimate a model of light, medium, and heavy commercial vehicle movements within the region.

Speaking the Same Language: Cross-walking Truck Classification Systems for Efficient Freight Modeling

Agencies rely on regional travel demand models to estimate current and future truck movements, which are calibrated and validated using external data sources such as truck classification counts. However, these data sources often employ different vehicle classification systems, making direct comparisons challenging. This study reviews common truck classification schemes used in the U.S. and develops a crosswalk methodology to facilitate data integration across different systems.

From Diesel to Electric: Implementing Electric Truck Mode in Statewide Freight Forecasting

California’s freight sector is undergoing significant changes due to regulatory requirements aimed at reducing emissions and improving the sustainability of goods movement at a very fast pace. The California Statewide Freight Forecasting and Travel Demand Model (CSF2TDM) plays a key role in evaluating the impacts of various scenarios by forecasting commercial vehicle travel flows and analyzing the interaction between truck movements, and changes in transportation infrastructure. The CSF2TDM integrates socioeconomic factors, land-use changes, and multimodal infrastructure investments to evaluate the effect of various policies on vehicle miles traveled and on-the-road emission. Given the rise of electric vehicle (EV) adoption, incorporating electric trucks into this model is essential for evaluating future transportation scenarios, energy use, and emissions impacts.

• 8:30 – 10:00 AM

• Thomas H. Swain Room