In a National Transit Institute course on “Coordinating Land Use and Transportation,” co-taught by Robert Cervero, Uri Avin, and the PI on this project, the analytic tools session began with a hypothetical: assume that all households, jobs, and other trip generators are concentrated in a walkable village rather than segregated by use and spread across a traffic analysis zone in the standard suburban fashion. The instructor then asks: How would the outputs of conventional four-step travel demand models differ between these two future land use scenarios. The answer, to most participants’ surprise, was “Not at all.”
Conventional four-step models, used by virtually all metropolitan planning organizations (MPOs), state departments of transportation and local transportation planning agencies to forecast future travel patterns and develop long-range transportation plans, are the basis for long-range transportation planning in the United States. Their importance for project selection cannot be overstated. These models currently are underspecified, which is to say that important variables are omitted. In particular, conventional models fail to fully account for local land use patterns, street network designs, and urban design features—indeed, the entire built environment at the scale of a neighborhood or activity center. In many four-step models, vehicle ownership is treated as a function of sociodemographic variables only (or largely), and the phenomenon of car shedding as the built environment becomes more compact is not accounted for. In many models, only trips by vehicle are modeled, and trip rates are related only to sociodemographic characteristics of people, not characteristics of place. Bicycling, in particular, is seldom treated as a separate transportation mode. In nearly all four-step models, households, jobs, and other trip generators are assumed to be located at a single point, the zone centroid, rather than spread across the traffic analysis zone, and the entire local street network is reduced to one or more centroid connectors to the regional street network. This precludes the modeling of intrazonal travel in terms of the local built environment. In the conventional model, daily traffic volumes are factored to obtain peak hour volumes without regard to the phenomenon of peak spreading as development becomes more concentrated and congestion increases. While there are other ways in which conventional travel demand models fail to account for land use-travel interactions, these four are the focus of this proposal.
With this proposal, we seek to develop and implement car shedding, intrazonal travel, walk and bike mode choice, and peak spreading models that can be used in conjunction with a conventional four-step model to capture neglected effects of the built environment on travel behavior. These models will be calibrated with data from our 28-region household travel database, the largest household travel database of its sort ever assembled, with over 92,889 households and 924,823 trips. This database has been linked to built environmental data for buffers around geocoded trip ends. These models will pre-process inputs to the four-step process and/or post-process outputs. They will be incorporated into the Wasatch Front Regional Council and Mountainland Association of Governments’ (our MPOs) four-step model and, based on this case study, will be offered to other MPOs for incorporation into their models. We have WFRC, MAG, UTA, and UDOT’s support to do this work. It best aligns with the NITC theme of Integrating Multimodal Transportation and Land Use.