The Puget Sound Regional Council has a region-wide multi-modal transportation demand forecasting model which supports the regional transportation plan Destination 2030. The Regional Council has incorporated new criteria regarding climate change in the evaluation of alternatives based on environmental policies established in the Vision 2040. To support that analysis, we developed five short-term travel model improvements that provided additional sensitivities and accuracies in the travel demand model outputs:

• Vehicle Assignment: Emissions models are dependent on accurate speeds and volumes from the regional travel demand models. The PSRC regional travel demand forecasting model speed validation required more rigorous standards to provide more accurate input to emissions models. The aggregate, regional nature of the PSRC travel model limits the ability of the model to accurately predict impacts from bottlenecks and queues on the roadways, but we included a reliability factor for freeways and an estimate of intersection delay for arterials which enabled improved speed validation by facility type.

• Tour Generation: The new activity generator model provides sensitivity to congestion, tolling, trip chaining, density, accessibility, urban design, age, and life cycle that were not possible before. These variables can clearly affect whether to make a trip or not (including substitutions for working at home, shopping on the internet, etc.) and how many trips and stops are needed to meet daily requirements for activities.

• Mode Choice: As the Puget Sound region moves from a primarily bus-oriented transit system to a mixed bus and rail system, there is a greater need to explore more detailed mode choice models to ensure that the models can accurately predict the modal shifts resulting from new modes. In addition, there is an interest in improving the accuracy of the current ferry mode in the regional model. We separated fares and service by mode in a nested logit model structure to allow for differences in reliability and convenience by mode.

• Walk Trips: Walk trips has been a potential source of error in the model in the past due to their short trip lengths and limited data to identify walk trips. They do, however, have a potentially large impact on emissions because shifting from a short auto trip to a walk trip can reduce emissions. Current mode choice models account only for walk time in estimating walk trips, when urban design, street connectivity, and mixed land use can impact walk trips as well. We used new data sources to create walkability factors, including measures of intersection density, retail floor area, and mixed land uses for each traffic analysis zone to improve the walk, bike, and transit modes in the mode choice model.

• Costs of Driving: The need to accurately represent the cost of driving is very high because these factors have a significant impact on traveler’s modal choices. Both parking and fuel costs are estimated for input to the models and both can fluctuate widely and be affected by statewide and national factors, which are outside the sphere of influence of PSRC and its members. Nonetheless, it is important to understand the potential impacts of increasing or decreasing costs and their ultimate impact on emissions. We tested the sensitivity of the model to a range of parking costs and gas prices from conservative to a realistic high end. These ranges were used to test the sensitivity of the model and predict the potential impacts on vehicle miles traveled and emissions.