Rolling horizons bus fleet allocation, holding control, and transit rescheduling strategies
The purpose is to increase the coordination among running buses, avoid vehicle bunching, and obtain the accurate evaluation of bus timetable
Salicru et al. [35]; Steiner and Irnich [36]; Zhang et al. [37]; Ma et al. [38]
Passenger travel demands extracted from multisource traffic datasets
Smarter computational methods were provided to reduce operational costs and improve the server level of bus timetable
Domschke [39]; Ceder et al. [40]; Eranki [41]; Liu et al. [42]; Ibarra-Rojas et al. [43–45]
Bus line network, route choices of passengers, waiting time at nodes, and the operational costs
They developed a series of models to represent the route choice behaviours of various passengers and minimize the operational cost of bus timetables
Wong et al. [46]; Shafahi and Khani [47]; Kang et al. [48]; Guo et al. [49, 50]; Chu et al. [12]; Abdolmaleki et al. [51]
Trains’ run times, station dwell times, interchange waiting times of all passengers, transfer redundant time, and the network accessibility
A series of nonlinear programming models were provided to achieve the synchronize timetables in the transit network and improve the transfer efficiency of passengers
