Optimal allocation of vehicles to bus routes using automatically collected data and simulation modelling
place - north america, place - urban, mode - bus, technology - automatic vehicle monitoring, infrastructure - fleet management, organisation - contracting, operations - performance, planning - service improvement, planning - service quality
Fleet allocation, Vehicle allocation, Running time variability, Simulation, Bus transit, Public transportation
Monitoring the service quality of high-frequency bus transit is important both to agencies running their own operations and those contracting out, where performance measures can be used to assess contract penalties or bonuses. The availability of automatically collected vehicle movement and demand data enables detecting changes in running times and demand, which may present opportunities to improve service quality and fleet utilization. This research develops a framework to maximize service performance in a set of high-frequency bus routes, given their planned headways and a total fleet size constraint. Using automatically collected data and simulation modelling to evaluate the performance of each route with varying fleet sizes, a greedy algorithm adjusts allocation toward optimality. A simplified case study involving morning peak service on nine bus routes in Boston demonstrates the feasibility and potential benefits of the approach. A potential application is automated detection of routes operating with insufficient or excessive resources.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Sánchez-Martínez, G.E., Koutsopoulos, H.N., & Wilson, N.H.M. (2016). Optimal allocation of vehicles to bus routes using automatically collected data and simulation modelling. Research in Transportation Economics, Available online 15 October 2016. In Press, Corrected Proof — Note to users.