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In order to provide the guideline for bus drivers to adjust speed to minimize scheduled deviation,the method for setting bus scheduled travel time is proposed.Firstly,multistate model is introduced to fit historical travel time data and identify different service states.Based on the calibrated travel time distribution parameters,an optimization model is proposed,followed by a Monte Carlo(MC)simulation based genetic algorithm(GA)procedure to obtain the optimal scheduled time.A case study from a fixed bus route from Shenzhen is used to demonstrate the model applicability.The sensitivity analysis is conducted to study the effects of parameters setting on optimal slack time for each segment.The results show that multistate model fits travel time under peak hours better than Lognormal distribution,and the length of scheduled travel time basically reflects travel time reliability.
In order to provide the guideline for bus drivers to adjust speed to minimize scheduled deviation, the method for setting bus scheduled travel time is proposed. Firstly, multistate model is introduced to fit historical travel time data and identify different service states. travel time distribution parameters, an optimization model is proposed, followed by a Monte Carlo (MC) simulation based genetic algorithm (GA) procedure to obtain the optimal scheduled time. A case study from a fixed bus route from Shenzhen is used to demonstrate the model Applicability. The sensitivity analysis is conducted to study the effects of parameters setting on optimal slack time for each segment. The results show that multistate model fits travel time under peak hours better than Lognormal distribution, and the length of scheduled travel time substantially represented travel time reliability