Project Summary
Transportation Network Companies (TNCs) have been touted by some as a possible means to encourage more transit ridership by providing a better connection to and from transit stations. TNC companies, like Uber and Lyft, however, are often inaccessible to certain groups, such as individuals without smartphones. Moreover, the tendency of TNC vehicles to double-park when loading and unloading passengers can add to traffic congestion, as do their “empty-miles” (i.e., time spent cruising without a passenger) while awaiting new fares. TNCs can also compete for trips with public transit which can erode transit ridership and precipitate reductions in service that beget further ridership losses. Declining transit service may ultimately produce gaps in mobility that cannot be filled by TNC vehicles that have much lower passenger-carrying capacities. These negative effects fall hardest on the transit dependent and other disadvantaged groups. This project will develop a system that better coordinates transit and TNC operations. The research team will explore the effect and interaction of policies that will help align reliable TNC first- and last-mile services to/from transit stations with fewer negative impacts. The project will explore the effect of establishing mandatory curbside boarding or off-street TNC dwell zones near transit, which would eliminate most door-to-door TNC services in these areas. The research team will also explore the effect of additional policies such as installing public communication devices in these zones to allow people without smartphones to use the system, and whether disincentives to waiting or cruising, such as mandatory parking rules, or charging TNCs high empty-mile fees, would improve the performance of such zones. The team will also examine whether those empty-mile fees could support a program to offer transit users subsidized first- and last-mile service to and from designated transit stations. A model will be formulated to optimize the system design and operation, building on previous works by the research team. The model will be able to recommend a neighborhood’s number of dwell zones, each zone’s vehicle-holding capacity and the necessary fees and subsidies to ensure that TNCs allocate their resources to serve the public as envisioned. The models will also estimate measures of performance, such as travel times and costs and take account of local conditions such as: neighborhood size, travel demand, the location of transit stations and various unit costs. A separate model will assess the system’s impact on traffic. Models will be developed for a wide-range of community forms and tested against many simulations, including a detailed case study.