Abstract
Providing quality transit service to travelers in low-density areas, particularly travelers without personal vehicles, is a constant challenge for transit agencies. The advent of fully-autonomous vehicles (AVs) and their inclusion in mobility service fleets may allow transit agencies to offer better service and/or reduce their own capital and operational costs. This study focuses on the problem of allocating resources between transit patterns and operating (or subsidizing) shared-use AV mobility services (SAMSs) in a large metropolitan area. To address this question, a joint transit network redesign and SAMS fleet size determination problem (JTNR-SFSDP) is introduced, and a bi-level mathematical programming formulation and solution approach are presented. The upper-level problem modifies a transit network frequency setting problem (TNFSP) formulation via incorporating SAMS fleet size as a decision variable and allowing the removal of bus routes. The lower-level problem consists of a dynamic combined mode choice-traveler assignment problem (DCMC-TAP) formulation. The heuristic solution procedure involves solving the upper-level problem using a nonlinear programming solver and solving the lower-level problem using an iterative agent-based assignment-simulation approach. To illustrate the effectiveness of the modeling framework, this study uses traveler demand from Chicago along with the region's existing multimodal transit network. The computational results indicate significant traveler benefits, in terms of improved average traveler wait times, associated with optimizing the joint design of multimodal transit networks and SAMS fleets compared with the initial transit network design.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2-20 |
| Number of pages | 19 |
| Journal | Transportation Research Part C: Emerging Technologies |
| Volume | 113 |
| DOIs | |
| State | Published - Apr 2020 |
Funding
Partial funding for this work was provided through a doctoral fellowship from the Brazilian National Council for Scientific and Technological Development (CNPq) for the first author. Partial funding was provided through an Eisenhower fellowship from the US Department of Transportation for the second author. Additional funding was provided by the Northwestern University Transportation Center. The computational experiments were supported in part through the computational resources and staff contributions provided for the Quest high performance computing facility at Northwestern University. The authors are grateful to the remarks and comments provided by four thorough and thoughtful referees, whose suggestions have greatly improved the present paper. The authors remain responsible for all findings and opinions presented in the paper. Partial funding for this work was provided through a doctoral fellowship from the Brazilian National Council for Scientific and Technological Development ( CNPq ) for the first author. Partial funding was provided through an Eisenhower fellowship from the US Department of Transportation for the second author. Additional funding was provided by the Northwestern University Transportation Center . The computational experiments were supported in part through the computational resources and staff contributions provided for the Quest high performance computing facility at Northwestern University. The authors are grateful to the remarks and comments provided by four thorough and thoughtful referees, whose suggestions have greatly improved the present paper. The authors remain responsible for all findings and opinions presented in the paper.
Keywords
- Bi-level programming
- Network modeling
- Shared autonomous vehicles
- Simulation
- Transit network design
ASJC Scopus subject areas
- Transportation
- Automotive Engineering
- Civil and Structural Engineering
- Management Science and Operations Research
