Shared Mobility

In anticipation of pervasive onboard navigation and electronic payment associated with connected vehicle technology, universal dynamic tolling is a promising possibility for future congestion management. In order to take advantage of these advancements, planners must consider which metrics should be used for the selection and performance evaluation of tolls. This work considers two metrics: median travel time and reliability measured with the 80th percentile travel time index. Each metric is tested for the identification of candidate tolling facilities and for the evaluation of the toll’s...

App-based ridehailing services such as Uber and Lyft are growing rapidly and serving more trips in large U.S. cities than conventional taxicabs, on which people with disabilities have historically depended. Analyzing the 2017 National Household Travel Survey, we found that adults with disabilities use app-based ridehailing at a much lower rate than adults without disabilities. This is partly because people with disabilities are older, have lower incomes, and live less in larger cities. But even when controlling for these factors, having a disability predicts lower use of app-based...

The rise of transportation network companies (TNCs) such as Uber, Lyft and Didi Chuxing has been well documented, and is viewed with concern by some policy makers and planners. Some have advocated regulating TNCs to address perceived problems, which include unfair competition with existing taxis, a perception that TNCs may be less safe than conventional taxis, road congestion caused by a proliferation of ride-hailing vehicles, and a belief that TNCs may reduce transit ridership. Possible regulations to address these problems include background checks for drivers, safety standards,...

California’s SB 1014 (Clean Miles Standard) mandates ridehailing fleet electrification to reduce emissions from vehicle miles traveled, posing financial and infrastructure challenges for drivers. This study employs a mixed-methods approach, including expert interviews (n = 10), group discussions (n = 8), and a survey of full- and part-time drivers (n = 436), to examine electric vehicle (EV) adoption attitudes and policy preferences. Access to home charging and prior EV experience emerged as the most statistically significant predictors of EV acquisition. Socio-demographic variables,...