We offer a wide range of services with a common goal: To combine analysis, research, and visual storytelling to support practical, defensible policy and planning. Our goal is to arm you tools, know-how, and technical problem solving, while also making complex and nuanced topics approachable for any audience.
Below are some examples of how we can help you go from data to decision-making.
Access and Quantitative Equity Analyses
The goal of a transportation system is utlimately to connect people to the destinations they wish to reach and to therefore participate in the activities they wish to participate in. Access to opportunity measures let you quantify how many opportunities are within a reasonable distance, or how far away important destinations are from someone's place of residence. These measures connect the quality of the transportation system with the land use patterns in a city to provide a big-picture understanding of how useful a system actually is in a city or regional context.
We can also measure how this access is distributed among population groups to learn about systemic gaps in the provision of transportation among socioeconomic and sociodemographic groups. With this information transportation planners and advocates can work to close these gaps and move towards more equitable and just transportation systems for all.
Here are some situations in which you might want to conduct an access and equity analysis:
- To identify existing gaps and barriers: Find areas in your city or region where access to opportunities by transit or other modes is hindered by poor service or land use. See gaps in service between demographic groups. The TransitCenter Equity Dashboard story page for Washington, D.C. is an example of how gaps in service between groups can be identified.
- To measure the impact of transportation projects: Proposed upgrades or other transportation projects can be measured against existing conditions or other alternatives to see how the proposed project is changing the equity of access to opportunities. The Equity Evaluations of Transport Futures Handbook we developed in partnership with Mobilizing Justice provides an example of how the outputs of transportation demand mdoels can be used to evaluate equity.
- To measure the impacts of changing land use: Rezoning, gentrification, and other land use policy changes can impact the level of access within a city. Using model outputs of changing land use, we can determine how different groups might be affected by these changes.
Performing these analyses requires determining the appropriate destinations to measure, the appropriate mathematical formulas of access to use, and the appropriate demographic groups to study. These decisions are dependent on the priorities and data availability of each specific region. We have experience developing best-practice guidelines and adapting measures to a wide variety of regions and destinations for specific contexts.
Reliability and Crowding
The reliability of a transit system consistently ranks at or near the top of factors impacting customer satisfaction with transit systems, and since the COVID-19 pandemic discomfort with vechile crowding has grown significantly. Using data commonly collected by transit agencies we can develop tools to measure detailed and system-wide relaibility, and provide crowding analysis of routes. Some examples include:
- Advanced and nuanced measures of reliability: Typical on-time performance measures don't effectively capture what's happening at the stop and route level. There are better ways to measure and visualize transit reliability that can help diagnose problem areas on routes and identify the need for schedule adjustments.
- Crowding estimation and prediction: Being able to estimate and predict crowding on routes can be useful both for customer safety and for general satisfaction. This information can be estimated using automated passenger counter data and can be communicated to users or to dispatchers who can adjust routes.
- Passenger-based reliability measures: Using new data sources such as WiFi connections we can better understand the actual passenger experience from start to finish, including variations in trip reliability and experience over time and between specific origins and destinations.
Demand and Use Patterns
Planning a useful transportation system requires advanced knowledge of where people travel, how they travel, and how changes in the transportation system might affect that travel. We can help you use data analytics and demand modelling to:
- Learn about travel patterns: Travel surveys can be supplemented with data such as cell phone traces and WiFi connections to build origin-destination demand matrices as well as trip-level information.
- Measure the impact of new projects: Translating demand into use patterns (trip assignment) is the last stage of the traditional transport modelling process, but is the most relevant for measuring actual changes due to new infrastructure. We can help you accurately assign transit, cycling, and other modes.
Real-Time and Disruption Management
Responding to incidents quickly and providing useful information to travellers quickly is key to building and maintaning trust in any transportation system. Using real-time and historical information we can help you:
- Leverage historical information to predict and add context to emerging disruptions: Use historical information to predict incident durations, coordinate response, and run scenario planning. One example of this is the use of historical delay logs to predict incident duration and find incidents with similar characteristics in the past.
- Implement tactical adjustments: With advanced data analysis, prediction, and dashboarding, you can get a clearer picture into your transit operations and make adjustments to opeartions at a finer detail. These smaller interventions can add up to large opeartional and customer time savings.
Dashboarding and Visualization
Made-for-you dashbaording and visualization tools can help you get the information that matters to you out of the data you have. Key benefits of good data visualizations include:
- Having the right amount of nuance: Decision makers often encounter information that is either too broad to really understand the situation, or too technical to absorb in their limited time. Finding the right amount of nuance can lead to more defensible decisions and a greater sense of confidence from the reader.
- Exploratory learning through interactivity: Allowing people to find themselves and their stories in the data without being overwhelmed with its complexity builds confidence and trust in the work you do. We can build cusomtized interactive visualizations to support the communication of complex topics. Examples include the story pages of the TransitCenter Equity Dashboard and visualizations of VIA's reliability.
If you would like to learn more about these or any other services we might be able to provide, get in touch to find how we can help.