Finding ways to boost transportation access for underserved populations can unlock broad social benefits. Micromobility programs, including bikesharing, offer scalable solutions. National, state, and regional housing and urban development agencies promote affordable housing and transit-accessible developments by funding programs such as the Low-Income Housing Tax Credit and Community Development Block Grants. However, these efforts are not always coordinated and the physical distance between affordable housing and transit access continues to grow. The problem is compounded by low car ownership rates in lower income urban communities. These circumstances have led to inequitable mobility access. To correct course, pairing affordable housing developments with reliable transit services is essential. This practice can increase equity and accessibility. A team at the University of California, Davis, conducted a case study in Sacramento, California, to explore bikesharing as an option for connecting affordable housing residents with transit services. This brief summarizes the findings from that research and provides implications for the field. 

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Last-mile delivery, in which companies deliver goods to the end consumers, is one of the costliest segments of the supply chain and can generate significant emissions. The demand for last-mile delivery has grown in recent decades because of the emergence of e-commerce, which has reshaped consumer behavior and how companies distribute goods. E-commerce has consistently been growing for more than a decade, and growth intensified during the COVID-19 pandemic. Although e-commerce is still in a fast growth phase, there is little understanding about how much it will grow, how it will impact the transportation system, and how these impacts might differ geographically. Researchers at the University of California, Davis developed a forecasting model to quantify the potential impacts of future e-commerce on emissions and transport activity under different scenarios with assumptions about penetration levels of various technologies (e.g., electrification, rush deliveries, crowdshipping, and automation/efficiency improvements). The researchers implemented the forecasting tool in six large metropolitan areas: New York, Los Angeles, San Francisco, Dallas, Washington D.C., and Chicago. These analyses can help planning agencies and local governments to better understand and manage the potential impacts of e-commerce.

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