New tools and data sources have begun to change the way we think about and plan for meeting people’s transportation needs. Accessibility analysis lets us measure transportation performance in terms of people’s ability to reach destinations instead of simply how fast cars move or whether transit runs on time. Trip-making data, which come from smartphones, navigation devices, and GPS-enabled vehicles, let us understand people’s travel patterns and trip characteristics in detail without relying on costly travel surveys or complex travel demand models.
Connecting Sacramento is the first study to incorporate both technologies, including data from multiple sources, and assess how they can be used together to guide transportation- and land use-related decisions. This study focused specifically on opportunities to improve first- and last-mile connections to light rail transit in Sacramento, but its findings are widely applicable.
Major Findings
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Vehicle trips
Using StreetLight Data, this study identifies personal vehicle trips that run along light rail lines, many of which could instead be made by transit. Many of those trips begin Downtown, just south of Downtown along the Blue Line, and near several stations along the Gold Line.
Light rail trips and mode share
Using data from Teralytics, this study reveals the origins, destinations, and mode share of light rail trips. As with StreetLight Data, this study only considers trips that begin and end near transit stations (precluding many park-and-ride trips). For example, only 1.4% of trips beginning just south of Butterfield station are made by light rail (compared to 5% in other nearby areas). This area includes several large office buildings served by abundant parking, which likely encourages driving and makes walking to the station less appealing.
Pedestrian trips
Using StreetLight Data, this study reveals the origins and destinations of walking trips to and from light rail stations. At the time of this study these methods were still in a trial phase, but trip metrics based on those methods are incorporated into the study on that basis.
Transit accessibility metrics
To evaluate transit accessibility, we measure the number of jobs accessible by transit during the morning period (7-10 AM) based on the existing transit schedules. In this case, the reported number of jobs is decay-weighted, meaning that nearby jobs are assigned more utility than jobs further away, based on decay functions derived from the 2009 National Household Travel Survey (NHTS) in the state of California. For example, a job within 10 minutes counts 100 percent; a job within 30 minutes counts 70 percent; and a job within 60 minutes counts 40 percent. This measure lets us evaluate existing accessibility and quantify the impacts of accessibility improvements.
Accessibility impact scores
Accessibility impact scores are developed to identify blocks that could benefit the most from improved connections to existing transit stations. This measure suggests that impactful connections could be added near Zinfandel station, Swanston station, Meadowview station, and others. A direct connection is not always possible, so the actual achievable travel time reduction must be calculated separately, based on project-specific details.
Other applications
Several other important applications are highlighted in this study, including:
• Using StreetLight Data to analyze vehicle trips to and from light rail parking lots. In many cases, people drive short distances suggesting they might be able to walk or bike.
In other cases, shuttles and ridesharing services might be reasonable alternatives.
• Using accessibility metrics identify transportation equity issues.
This study, led by the State Smart Transportation Initiative with the Lincoln Institute of Land Policy, was sponsored by TransitCenter with additional support from the Barr Foundation and Planet Bike. Partners include the Sacramento Council of Governments, the City of Sacramento, Sacramento Regional Transit, Caltrans, the Sacramento Downtown Partnership, Citilabs, StreetLight Data, and Teralytics.