Transportation demand management aids equity and climate plans

Transportation demand management aids equity and climate plans
By Lainey Benson and Frank T. Mongioi, Jr.
Vice President, Transportation and Smart Mobility
Jan 27, 2022
5 MIN. READ
Our analysis of guaranteed ride home and emergency ride home programs shows they're critical tools used by underserved and disadvantaged populations to get to and from work.

More than 30 states have released a climate action plan or are currently writing or revising one. These plans typically include greenhouse gas emissions reduction targets and specify actions the states can take to meet those objectives. While these climate action plans may also include resilience strategies, clean energy targets, and economic and social goals—many states are also putting a strong emphasis on equity and unserved/underserved communities and populations.

Transportation demand management (TDM) and sustainable mobility strategies are programs that help reduce traffic congestion; improve air quality, mobility, and connectivity; and support a more efficient transportation system. Underserved communities and disadvantaged populations utilize many TDM programs, including car/vanpool matching, transit itinerary planning and assistance, and in particular guaranteed ride home (GRH)/emergency ride home (ERH) programs. GRH/ERH programs provide users of carpools, vanpool, and transit with a free and reliable ride home when an unexpected life emergency arises.

Guaranteed ride programs are a staple in many TDM program toolboxes. Their core purpose is to increase transit use and ridesharing by removing the barrier of lacking access to transportation in the event of an emergency while at work. For example, many job opportunities involve swing, night, and weekend shifts when public transit is not readily available, and rail and bus services are often located some distance from work and home. Or an individual’s carpool driver may become unavailable for their trip home. This unreliability prevents many from foregoing single occupant vehicle travel to work.

Economic and environmental analysis

We evaluated a GRH program consisting of more than 6,000 enrolled members. This gave us a significant subset of total program members confirmed to be dependent on an alternative transportation mode (i.e., did not drive alone to their worksite) at least twice a week. To gain a more comprehensive understanding of the current circumstances—both economically and environmentally—of the communities in the program, we asked questions such as:

  • How are underserved communities qualitatively and quantifiably defined?
  • What percentage of the guaranteed ride home program members, by definition(s), are in an underserved/disadvantaged community and where are they?
  • Which employers are these members commuting to and what are their primary modes of transportation?
  • With this information, how can the program execute targeted outreach strategies to provide relevant alternative transportation resources as equitably as possible via community-based partnerships and more localized support?
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By general definition, a “disadvantaged community” is an area in which most of the population suffers from a combination of economic, health, and environmental burdens. Burdens can be poverty, high unemployment, air and water pollution, and/or high incidence of asthma and heart disease.

Not only is this a broad definition, but states and agencies differ in their specific criterion as to what statistically would make a community designated as “disadvantaged” or “underserved.” For the purpose of making this analysis as relevant to the local region as possible, we utilized a collection of four criteria-based definitions sourced from various state agencies and federal departments to serve as the study's four main categories, or layers.

Our analysis incorporated layers that were defined either by socioeconomic burdens, such as high poverty and unemployment rates, or by certain environmental stressors. Many agencies determine areas with high minority, low-income populations as Environmental Justice Communities due to the inequitable predisposal of environmental harms to such groups. Therefore, we incorporated Environmental Justice Communities as a layer in this analysis as well.

The statistical and geospatial results of this analysis, based on member’s home zip code, revealed a significant percentage of members affected by such socioeconomic and environmental thresholds registered with the program:

What percentage of TOTAL GRP members are located within disadvantaged communities

In addition to identifying the percentage of members we had in each classification of an underserved community, as seen on the bottom of the chart above, we compiled data to look at a wider spectrum of the subject group by identifying the percentage of members who met one or more of the thresholds across any of the categories. We completed this categorical member data analysis on a regional level as well in order to provide further insights for regional program teams.

Distribution of GRP member home location by disadvantaged communities

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As a reminder of the importance of understanding your program’s member base, the chart above shows that this GRH program serves more individuals that are disproportionately affected by disadvantaged attributes than not. In fact, 75% of members meet at least one of the 6 listed criteria and that most of the member base are located in what are defined as Environmental Justice Communities or economically distressed areas.

Using data to inform communications

Our analysis also looked at travel mode patterns for applicable members on a category-by-category level. That is, what are the common travel modes for members in Region X who live in an economically distressed community? Compiling this information better informed program teams on which modes are most used in their region to further understand the community transportation trends.

This data presents targeted exploration opportunities for outreach teams. For example, identifying which underserved communities possess a high percentage of carpool members—possibly due to lack of transit access—can lead to more specific conversations with local community leaders or employers about additional first-mile/last-mile transit options or preferred parking at worksites to support ridesharing commuters.

Creating visual and interactive elements, such as a statewide map with each of the definitions geo-spatially highlighted, allows your program’s outreach team to identify specific geographic areas that are facing such socioeconomic and environmental risks. Once identified, outreach teams can develop strategic and direct outreach plans that further engage with groups located in these specific communities and provide relevant transportation resources and/or solutions.

Many state and federal departments are beginning to analyze their public programs and services with a brighter spotlight on the equitable accessibility of their resources to historically underserved populations. There is immense opportunity for a deeper community-based understanding, which is paramount when considering the impacts and needs of climate action. Transportation is a key component to such efforts. Taking a deeper look at the populations who are more dependent on TDM resources, such as GRH programs, can provide valuable insights to be used for a more equitable targeting of resources, community-based partnerships, and mobility solutions.

Improving the transportation system for all is a collaborative effort, requiring the partnering of local municipal departments, state agencies, and community-based organizations. Exploring how TDM programs are reaching underserved populations and creating new outreach models that will extend the reach of alternative transportation resources even further must be crucial for states to consider when pursuing climate action plans.

Meet the authors
  1. Lainey Benson, Transportation and Smart Mobility Specialist
  2. Frank T. Mongioi, Jr., Vice President, Transportation and Smart Mobility

    Frank has more than 25 years of experience in transportation demand management and mobility programs, focusing on optimizing client programs, navigating change, and streamlining innovation and improvements. View bio