Research On Train Operation Optimization Of Urban Rail Transit Based On Interoperability

The network of urban rail transit system develops fast in nowadays.The disadvantages of current operation mode are getting more and more prominent,such as the low utilization rate of line resources and inability to meet the diverse travel needs of passengers,etc.Therefore,it is a general trend to realize deep network operation based on interoperability between different rail transit lines.In the condition of interconnected network operation,this dissertation focuses on the optimization problem of train operation plan and train schedule in urban rail transit.Models and algorithms are proposed to achieve the inter-line coordination and improve the passenger service level.The main contents include the following four parts:(1)The existing literature of urban rail transit in current operation mode is summarized.The characteristics of passenger flow,the line capacity and train plan under interconnected network operation are analyzed and compared.Especially,the necessary of cross-line trains running on network have been deeply discussed.(2)Train operation plan optimization under network operation based on interoperability.The classification of the passenger flow is defined.The number of cross-line trains that can be inserted is analyzed.On the basis of full consideration of various constraints such as the passenger flow demand,line capacity,and train tracking interval,with the objective function of minimizing the total operating cost of passengers and the company,an optimization model for train operation plan under interconnected network operation is constructed.Then we design a genetic algorithm and verify the model and algorithm through the examples.(3)In order to study the train coordination problem under interconnected network operation,the coordination of train operation sequence and train connection of different lines are deeply analyzed.The coordination of the train schedule and the transfer passengers’ waiting time are used as the objective function to construct the optimization models.Then,algorithms to determine the optimal line schedule are designed.The models are optimized based on the CPLEX solver and genetic algorithm,and the model and algorithm are verified through the design examples.(4)Based on the real line data,the effectiveness of the model and algorithms are further verified.The solution is analyzed from the perspectives of passenger directness,transportation efficiency,passengers’ travel cost,and operating cost.The analysis of the solution shows that under proper passenger flow intensity,the network operation under interconnected has greater advantages for both passengers and operating companies: it can effectively reduce overall passenger travel costs,improving passenger travel directness,improve company transportation efficiency,improve passenger travel satisfaction and inter-line coordination of trains.