Multimodal mobility systems: joint optimization of transit network design and pricing

摘要: The performance of multimodal mobility systems relies on the seamless integration conventional mass transit services and advent Mobility-on-Demand (MoD) services. Prior work is limited to individually improving various transport networks' operations or linking a new mode an existing system. In this work, we attempt solve network design pricing problems en masse. An operator (public agency private operator) determines frequency settings system, flows MoD service, prices for each trip optimize overall welfare. A primal-dual approach, inspired by market literature, yields compact mixed integer linear programming (MILP) formulation. However, key computational challenge remains in allocating exponential number hybrid modes accessible travelers. We provide tractable solution approach through decomposition scheme approximation algorithm that accelerates computation enables optimization large-scale problem instances. Using case study Nashville, Tennessee, demonstrate value proposed model. also show our reduces average runtime 60% compared advanced MILP solvers. This result seeks establish generic simple-to-implement way revamping redesigning regional order meet increase travel demand integrate traditional fixed-line with demand-responsive