Optimizing Demand Responsive Bus Operation Strategies

An efficient,convenient,green,comfortable,and demand oriented public transit system should be able to reduce energy consumption,alleviate traffic congestion and decrease emissions.Such a system helps to construct a livable urban environment.With the increasing expansion of urban scale and the more refinement of urban functional zones,the bus passenger demand distribution of a city or region apparently presents a temporal and spatial imbalance.However,a single full route operation strategy(FRO)used by most cities obviously can not meet such a characteristic of passenger demand distribution.This work,therefore,from the perspectives of bus planning and operations,investigates an optimization of multiple operational strategies problem based on fixed bus routes/network.It aims to optimize the allocation of bus resources,and further to improve bus operations system efficiency by tailoring supply to demand in the best possible method.The main content of research is as follows:1)Based on fixed bus routes/network,this work develops an optimizing bus route operational strategies model and an optimizing bus network operational strategies model respectively with the same objective of minimizing the number of bus vehicles required,considering the serving stops of multiple strategies as variables.The proposed models can be solved by the outer approximation with both equality relaxation and augmented penalty(OA/ER/AP)algorithm coded in the optimization programming language GAMS.As a result,a combinational of operational strategies and their serving frequencies are obtained.These proposed models have applied to a case study of Line 23,Dalian,China,and an example of bus network respectively.The results show the use of multiple operational strategies could better accommodate to passenger demand and save the number of vehicles required,compared with using FRO strategy.2)Considering the relationship of demand,operational strategies,and fare,this paper establishes an integrated optimization model of multiple operational strategies and fare by maximizing the sum of user surplus and bus operator profit.Demand is considered as a function with respect to waiting time,in-vehicle time,fare,and in-vehicle crowding.In addition,a fare table has been presented which allows for a flat fare and a differential fare.For a differential fare,it is constructed on the basis of trip distance and achieved service levels.A bus line in the city of Dalian,China,line 26,is taken as a numerical example for applying the proposed model.The results indicate that an optimal combination of operational strategies integrated with a differential fare could more greatly improve bus operations system efficiency,than when strategies are optimized using a flat fare,or when FRO is optimized using a differential fare,if the value of an additional service fee parameter of a differential fare is less than a threshold.3)Vehicle scheduling as an important component of bus operation process,is related to bus operating cost and profit.Based on a given bus timetable,this work proposes a static vehicle scheduling method of DF-based multiple operational strategies with the objective of minimizing the number of vehicles required.First,based on this given timetable,DF vehicle scheduling graphs are constructed to recognize variable bus trips which are dispatched by using other strategies such as limited stop,short turn,mixed strategy,and deadheading strategy in order to reduce the number of vehicles required.Second,0-1 integer programming models with minimizing passenger travel time changes are formulated to determine serving stops of operational strategies used by bus trips.This proposed methodology has been tested with the data of Line 81,Paris,France.The results illustrate that it could reduce the number of vehicles required and improve vehicle scheduling levels.4)With the development of intelligent transportation technology,real time data of some routes such as vehicle position,the number of passengers in vehicle,traffic condition,et al.can be collected for dynamic vehicle scheduling of multiple operational strategies.This work develops dynamic vehicle scheduling models for different operational strategies,with the same objective of minimizing the sum of passenger travel cost and bus operator cost.To avoid passengers' confusion caused by vehicle serving stops changes,stops that a vehicle dispatched at the terminal should make on its route are determined by solving optimization models according to a given vehicle start time.Vehicle space-time travel graphs and Pareto efficient frontier graph are constructed based on obtained optimal solutions using different operational strategies.This proposed methodology has been examined with the data of Line 26 Dalian,China.The results imply that using multiple operational strategies not only enhances vehicle scheduling levels but also improves the distribution of headways between two vehicles along a corridor and thus reduces bunching.This thesis is closed with a summary plus a list of topics for future research.