Designing an Autonomous Service to Cover Transit’s Last Mile in Low-Density Areas

Abstract

Public transportation provides a safe, convenient, affordable, and environmentally friendly mobility service. However, due to its fixed routes and limited network coverage, it is sometimes difficult or impossible for passengers to walk from a transit stop to their destination. This inaccessibility problem is also known as the "transit last-mile connectivity problem." Such a lack of connectivity forces travelers to drive, thereby increasing vehicle miles traveled (VMT) on roads. The autonomous mobility-on-demand (AMoD) service, with characteristics such as quick fleet repositioning and demand responsiveness, as well as lower operational cost due to the elimination of operators' wages, has the potential to provide last-mile coverage where fixed-route transit can only provide limited service. This study presents research on designing an AMoD service to solve the transit last-mile problem in Greater Minnesota. After selection of the Miller Hill Mall (MMH) area in Duluth, MN, as the case study site, analysis on local transit services and demand data show that passengers may have to spend significant time walking and cross multiple streets to access stores from transit stops. To address this issue, an AMoD system for last-mile service was designed and integrated with the fixed route transit service. Novel mathematical models and AMoD control algorithms were developed, and simulation experiments were conducted for evaluation of the AMoD service. Simulation results showed that the AMoD service can improve transit quality of service and attract more riders to use transit to the MHM area, and therefore reduce the VMT in the region. These findings were consistent with the literature in that mode choice and first-/last-mile access were highly interdependent and AMoD can improve transit quality of service and reduce VMT. Research on riders' perception of AMoD service and field testing of the AMoD system using the developed models and algorithms are recommended to help agencies prepare for application of AMoD system in the region.