Impact of Transit Priority and Transit Autonomy on Vision Zero

Abstract

Vision Zero—the goal of eliminating traffic fatalities and serious injuries—is proving to be challenging for cities. At the same time, the field of autonomous vehicles (AVs) is rapidly evolving and will profoundly affect transportation systems. With a reduction in perceived cost of travel time, AVs will likely increase traffic. This thesis investigates how Seattle can pursue its Vision Zero goal in the context of the rollout of AVs. Informed by practitioner interviews, I modeled two key interventions: converting all buses to driverless operations across several different network designs, and implementing ubiquitous transit priority. I used the Puget Sound Regional Council’s Household Travel Survey data to create a multinomial logit model that predicts travel behavior. Then, I simulated trips accounting for changed transit travel time and the effects of congestion. I found that both interventions can reduce transit travel time by up to 33%, while transit mode share increased by only 2.5pp. The congestion effects of AVs and transit lanes reduced the average speed of vehicles in the city, resulting in a scenario that yields up to a 35% reduction in fatalities. These results suggest that policymakers should pursue policies that manage vehicle speeds first and foremost, and that faster, more frequent transit can be an effective way to keep people moving even if their personal vehicle is speed-constrained.