Transportation projects in major metropolitan regions can vary widely in the types of benefits that they provide and in the scales of those benefits. Travel forecasting models and related procedures can provide reasonable estimates of those benefits, and many benefits can be distilled into equivalent monetary benefits by the use of consumer surplus or other valuation approaches. In theory, those methods could also be used to prioritize projects for funding consideration. However, an approach that simply chooses projects that provide the greatest net economic benefits may not result in a mix of projects that most effectively accomplishes broad regional goals. This paper describes an approach to project prioritization that was developed to support stakeholder-based weighting of multiple goals and, for each goal, multiple measures. The approach uses the analytic hierarchy approach to develop weights for each goal and a conjoint-based method to estimate stakeholder weights for each measure. The approach was applied as part of Washington State's Puget Sound Regional Council's Transportation 2040 process and achieved the goals in VISION 2040, the long-range land use plan. Weighting exercises were conducted with two stakeholder groups, and the results were applied to a set of proposed ferry, rail, highway, and local road projects. This paper describes the details of this case study and provides observations and conclusions from the work. The principal findings of the experiments were that statistically robust modeling conducted in real time during planning committee meetings can improve the transparency, equity, and collaboration of the project prioritization process.

Smartphone-based household travel survey (HTS) studies to date have typically followed the two-part survey process that has historically been used for paper, computer-assisted telephone interviewing, and online HTS. In this two-part survey process, households provide demographic data in a recruit survey (part one) and record trips in a travel diary (part two) often at a later date. The Metropolitan Council, the planning organization serving the Twin Cities metropolitan area in Minnesota, has conducted a pilot study for their cyclical HTS, the Travel Behavior Inventory (TBI), that is one of the first large-scale fields of an all-in-one smartphone HTS design. For the 2018 TBI pilot, the traditional two-part survey was merged into a continuous survey experience within a smartphone app. The TBI pilot used a split sample to test this all-in-one design against a traditional two-part smartphone survey design. For the all-in-one design, households were invited to sign in directly to the smartphone application instead of first recruiting online or by phone. The pilot results provide a direct comparison of the two-part and all-in-one designs at the household-, person-, and trip-levels. The results showed a lower overall recruit and completion rate for the all-in-one design but showed clear promise for increasing representation of younger and lower-income populations—traditionally hard-to-reach groups who completed at a higher rate with all-in-one. The authors discuss several factors which may have contributed to the lower overall completion rate and describe planned updates for future waves of the TBI aimed at improving overall response while maintaining the developments that have improved representation from hard-to-reach groups.