Optimization Of Commuter Railway Timetable Considering The Balance Of Passenger Travel Efficieny And Train Energy Consumption

Metropolitan area division pattern of the central city,new cities and satellite cities have been formed during the accelerating urbanization process and the rapid expansion of cities.The urban population is gradually spreading to the new cities and satellite cities,generating a large volume of commuting travel demand.However,in the face of the huge commuting travel demand and tidal flow characteristics,the primary consideration lays in how to carry out scientific and flexible transportation organization and how to optimize the transportation capacity supply to match the passenger-travel demand.The existing research methods are mostly oriented to high-speed rail and subway scenarios,which are not sufficiently adaptable to commuter railway.This work focuses on the optimization on train timetables to meet passengers’ demand and improve passengers’ travel efficiency,while effectively suppressing the train energy consumption.Since the commuter railway is still at the developing stage in China,this work targets at obtaining optimized train timetables to meet the demands of timedependent passengers,considering the passenger travel efficiency and train energy consumption in a unified framework.The research work is of practical use from both the theoretical and the application points of view.The research contents can be divided into four sessions as follows:(1)This work reveals the composition,influencing factors,and inner relationship between passenger travel efficiency and train operation energy consumption of commuter railway.Starting from the objective of commuter railway timetable optimization,we first introduce the basic concepts,components of passenger travel efficiency,and equations on train operation energy consumption of commuter railway.Then we analyze the key factors and mutual-influence relationships influencing the passenger efficiency and train energy consumption,with the purpose of establishing the main research object.This session lays down the basis for the optimization research of train timetable in the following sessions.(2)The train stop plan and timetable under the variable number of trains are optimized in a collaborative manner.A mixed integer programming(MIP)model is established to improve the passenger travel efficiency and reduce the total train running time.Considering the stranded passengers at the station during the peak period,an integrated model is proposed where the passenger boarding,alighting,and detention processes are described in a unified framework.The model integrates the optimization of the train stop plan and timetable to achieve travel efficiency improvement,by minimizing passengers’ waiting time and passengers’ extra in-vehicle time.The passengers’ extra invehicle time is induced by train stopping time rather than averaging the passengers’ waiting time.Under the condition of variable number of trains and stop plan,the service frequency of trains and stations is included in the optimization model to meet the basic train service.Combining the mathematical characteristics of the integrated optimization model,the extended adaptive large neighborhood search algorithm(ALNS)is employed to solve the integrated model of train timetable and stop plan.The effectiveness of the model and algorithm is verified by numerical experiments.The integrated optimization model and algorithm is validated through case studies on real-world lines.The empirical results show that the proposed integrated optimization model of the stop plan and timetable can not only improve the passenger travel efficiency,but also reduce the train running time and achieve a balance between the passenger travel efficiency and the total train running time.Through the real-world-case analysis of the passenger oversaturation scene at the station,the integrated optimization method of the stop plan and train timetable is proved to be effectively adaptive to the oversaturated demand of the station,which can ensure the travel efficiency of passengers.(3)The train timetable that balances passenger travel efficiency and train energy consumption is optimized,taking the optimization of the energy-efficient train control as a breakthrough point.A unified framework for optimization of stop plans,timetables and speed curves under variable train numbers is constructed.With the goal of minimizing passenger waiting time,passenger in-vehicle time,and train energy consumption,an optimizing model for collaborative optimization of timetable,stop plan and speed curves is proposed.We design an adaptive large-neighborhood search(ALNS)algorithm composed of three groups of operators including train skip-stop,timetable optimization,and running time adjustment.At the same time,the train energy-efficient speed curve simulation optimization algorithm module based on dichotomy is applied,and the simulation optimization module is embedded in the adaptive algorithm.The effectiveness of the proposed model and algorithm is verified by numerical experiments.The real-world study results show that the proposed integrated optimization method of train energyefficient timetable can effectively reduce passenger waiting time,passenger in-vehicle time,and train energy consumption.It can balance the cost of train operation and the travel efficiency of passengers.(4)The train timetable that balances passenger travel efficiency and train energy consumption under the flexible marshalling is collaboratively optimized,taking the flexible marshalling as a further entry point.A collaborative optimization model of energy-efficient train timetable for commuter railway considering flexible marshalling is constructed.The model takes the time-dependent passenger demand as the input;it takes the formation,stop plan,timetable,and running time as the optimization variables.According to the research problem and the characteristics of the optimization model,the marshalling optimization operator is further designed to improve the S-ALNS algorithm proposed in this paper to solve the collaborative optimization scheme of the train energyefficient timetable.The model and algorithm are analyzed as well as verified by numerical experiments.Through real-world case studies,the optimization results of train timetable considering flexible marshalling can effectively be used to meet the passengers’ demand during different time periods.The optimization work has a significant positive effects regarding improving the train capacity and reducing the energy consumption.The optimized train timetable is effective in balancing passenger travel efficiency and train energy consumption.This work is oriented to the optimization issue of commuter railway train timetable based on time-dependent passenger demand,with the purpose of balancing passengers’ travel efficiency and train energy consumption.It carries out the optimization research of train timetable from multiple stages progressively,balancing the passenger travel efficiency and the train energy consumption.This work provides scientific methods for the development of commuter railways.