Assessing the Impacts of Development in the Transportation Network

Siva Srinivasan, Ph.D.
Assistant Professor, Civil & Coastal Engineering

The impact of a development (for example a shopping center) on the transportation system is traditionally captured in terms of the number of additional trips added to the network. While the trip rate is appropriate to capture the effect of a development locally (say at a near by intersection), it is not an adequate measure of regional impacts. For instance, two developments could result in the same number of additional trips, but one of them could be attracting these trips from much father away. In this case, it could be argued that the transportation-impacts of both these developments are not identical (as would be indicated by a purely trip-volume- based assessment); rather the one that leads to longer trip lengths effectively has a greater (negative) impact on the transportation system.  With increasing emphasis on growth management and the containment of urban sprawl, there is a need for the assessment of such macro impacts of development using methods that relate the built-environment patterns to trip lengths.  Further, there is a desire to moderate the energy consumed by the transportation sector to achieve energy-sustainability and to reduce the extent of greenhouse gas (GHG) emissions from vehicles. To achieve this goal without adversely affecting the quality-of-life of the people (broadly defined as the ability of people to satisfy their activity-participation needs), planners and policy-makers are exploring urban-design solutions such as mixed-use neighborhoods (i.e. residential, commercials, schools, retail). In order to assess the extent to which such land-use patterns can reduce the length of travel undertaken, it is necessary to quantify the relationships between land-use and trip lengths.

CMS researchers have recently built a spreadsheet-based tool for estimating the lengths of vehicle trips generated by various types of land use patterns. Travel data from the 1999 Southeast Florida Regional Travel Characteristics Study (about 5000 households) were combined with detailed land-use and roadway network data from the Miami-Dade, Broward, and Palm Beach Counties to build statistical models for trip lengths for different trip purposes. These models have been implemented in the spreadsheet-based tool.

As an illustration the tool is used to predict the lengths of home-based work (HBW) and other (HBO) trips produced in identical residential parcels that are located in three very different neighborhoods of the region: one in Pahokee, in rural Palm Beach County the second just outside the city of Palm Beach (suburban) and the third in downtown Miami. The residential parcel in the rural neighborhood produces the longest HBW (19.61 miles) and HBO trips (8.68 miles). The parcel in the urban location produces the shortest HBW (4.21 miles) and HBO (2.23 miles) trips. The suburban location in West Palm produced HBW trips of 6.72 miles and HBO trips of 3.85 miles. Overall, this example illustrates the ability of the models to predict the trip lengths reflective of the context in which the travel is taking place.

Further details at: http://cms.ce.ufl.edu/research/Steiner_CMS_2008-007_final.pdf