Collaborative Optimization of Urban Rail Timetable and Flow Control Under Mixed Passenger and Freight Transportation

With the development of the economy and society, ground traffic road congestion is serious, resulting in increased carbon emissions. Due to the advantages of energy saving, environmental protection, and emission reduction of urban rail transit, full use of the redundant transportation capacity of rail transit is currently a feasible solution to alleviate the pressure of ground cargo transportation and reduce carbon emissions. This paper studies the timetable and flow control problem under the mixed passenger and freight transportation mode. Firstly, a model for mixed passenger and freight transportation in an urban rail line is constructed, which takes the departure time of the train, the layout of the train carriages, and the number of passenger and freight demand allocated to the train compartment as the decision variables to minimize the waiting time of passengers and goods and the energy consumption of the train compartment, considering flow balance constraints, train capacity limitation, and timetable. To verify the validity of the model, Shanghai Metro Line 17 is taken as an example for empirical research, and the model is solved by the optimization solver Gurobi. The results show that the collaborative optimization method proposed in this paper has a good optimization effect and computational efficiency. Compared with the one-by-one solution method, the number of passenger and cargo delays can be significantly reduced. Collaborative optimization can reduce the number of passenger delays by 21.92%, the number of cargo delays by 9.73%, the average waiting time of passengers and cargo by 35.88%, 25.56%, and carbon emissions by 1.7% . This method can improve the load rate, reduce the waste of capacity during the peak period, and improve the safety and efficiency of rail transit operations. © 2023 Science Press. All rights reserved.