Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle

Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.

► Uncertainty in a combined land use and transportation model using Bayesian melding.
► Case study targets a controversy around the replacement of the Alaskan Way Viaduct.
► We analyze a predictive distribution of average commute times on 22 different routes.
► We compare two different policy scenarios including tearing down the viaduct.
► Hypothesis that removing the viaduct will increase travel times is not supported.