Light rail transit and bus rapid transit in the Twin Cities provide urban residents with fast, safe and reliable transportation. These transitways have the potential to attract more riders and further reduce automobile traffic, relieving the growth of congestion on nearby roads as people decide to be transitway passengers rather than motorists.
Because public transit, especially light rail, is highly subsidized by public funding, determining its effect on automobile traffic volume is essential for planners as they evaluate current operations. Reductions in automobile traffic growth must be accurately measured and supported with quantitative data for planners to effectively consider and anticipate future transitway expansions.
“The project highlights how a transit investment benefits other transportation modes. Similarly, the park-and-ride choice model provides insight into what is important to park-and-ride users, enhancing our ability to forecast future demand,” said Jim Henricksen, director, Travel Behavior Analysis, MnDOT Metro District.
MnDOT wanted to know how a transitway affects automobile traffic on nearby roadways. Further, the agency wanted to learn how park-and-ride users choose a location to park and take transit. Efficient and appealing park-and-ride facilities could greatly complement efforts to increase travelers’ use of transit services, allowing residents living beyond walking distance to transit to gain easy access to transit lines.
What Was Our Goal?
This project’s primary objective was to conduct a before and after study of changes in vehicular travel demand due to the Green Line light rail on roads in its vicinity, providing data-based evaluation and evidence to be used in the assessment of future projects. A second objective was to determine factors that influence people’s choices of which park-and-ride facilities to use and to develop a model for future planning.
What Did We Do?
Researchers first examined previously published works that analyzed effects of transit projects on automobile traffic volume. They found that most studies were limited by not accounting for confounding factors, such as changing transit supply and land use along roads. This finding informed researchers’ work for this project.
MnDOT provided annual average daily traffic data from before (2009-2010) and after (2015-2018) the opening of the Green Line light rail in 2014. The excluded intervening years covered the Green Line’s construction period when traffic was disrupted. For the analysis, researchers identified roads as influenced or not influenced by light rail.
They also categorized roads as principal arterial, minor arterial, collector roads and local roads. Higher road classifications correspond to higher traffic volume. In addition, land use along a road segment affects travel demand. Thus, researchers computed the areas of commercial use, industrial use, institutional use and residential use within a half-mile of roads considered. These aspects, as well as changes to bus route availability, required researchers to perform complex analyses that accounted for a wide range of variables. Their understanding of the dynamic nature of the situation allowed them to produce a nuanced, accurate result.
The park-and-ride research, conversely, relied on responses to Metro Transit’s on-board surveys from 2016. The on-board surveys provided trip attributes and demographic information about the respondents, helping researchers study their travel behavior and preferences; researchers used 1,895 park-and-ride trip records to develop and test a park-and-ride location choice model.
What Was the Result?
The Green Line reduced road traffic in the first two years of operations by 22%. However, the effect then decreased to 16% as land use and travel demand likely shifted with changing usage. Researchers noted that rail transit has a sizable effect on road traffic and its influence is dynamic. Because rail transit is more attractive than bus service to motorists, the Green Line dramatically enhances transit ridership along the corridor. Although the effect on road traffic appears to decrease over time, light rail improves system efficiency and traveler well-being. Overall, the entire system transports more people than before without increasing roadway traffic.
“The traffic analysis confirms the benefits of transitways in controlling traffic volume growth, helping transportation agencies make confident decisions about future transit projects,” said Alireza Khani, assistant professor, University of Minnesota Department of Civil, Environmental and Geo-Engineering.
Metro Transit’s survey of on-board users provided the basis for the park-and-ride model that researchers developed. Model results revealed that users consider time spent driving as four times more burdensome than time on transit. Users chose a travel path with a high proportion of time on transit, but they were not necessarily looking for the shortest overall travel time. Additional travel time was not as burdensome as some factors, such as transferring between transit routes. According to the results, transitways had a similar positive effect as three minutes less driving time. The survey was very illuminating and guided researchers in developing a model that could predict the park-and-ride choice of more than 64% of users when tested on a sample group.
MnDOT will use the project’s data and supporting findings in its transit evaluations and planning. The park-and-ride model will greatly assist planners in designing and locating facilities that are both appealing and convenient for transit users.