Dedicated bus lane network design under demand diversion and dynamic traffic congestion: An aggregated network and continuous approximation model approach
mode - bus, mode - car, ridership - demand, infrastructure - bus/tram lane, planning - methods, planning - integration, planning - network design, planning - route design
Network design, Public transportation, Macroscopic fundamental diagram
This paper proposes an integrated methodological framework to design a spatially heterogeneous bus route network and time-dependent service headways to serve travel demand that varies over time and space. Travelers choose to use either the transit mode or the driving mode (as well as travel paths in the corresponding modal network) that minimizes their equilibrium travel cost. In addition, transit routes involve dedicated bus lanes that occupy part of the city streets and affect the capacity reserved for private cars. Hence, roadway congestion depends on the transit route design, and its dynamic evolution is described by regional macroscopic fundamental diagrams. The proposed modeling framework consists of two parts: a bus network optimization module based on continuum approximation that produces optimal headways and local route spacing, and a dynamic aggregated network model that determines route choice, mode split, and user equilibrium conditions. An iterative solution algorithm is developed to solve the integrated model. Numerical experiments are used to demonstrate the applicability of the proposed modeling framework, and to conduct a careful analysis on the influence of the demand pattern on the transit network design, roadway congestion, and the overall system performance.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Petit, A., Yildirimoglu, M., Geroliminis, N., & Ouyang, Y. (2021). Dedicated bus lane network design under demand diversion and dynamic traffic congestion: An aggregated network and continuous approximation model approach. Transportation Research Part C: Emerging Technologies, Vol. 128, 103187.