An integrated optimization approach for passenger flow control strategy and metro train scheduling considering skip-stop patterns in special situations

In many special situations (epidemic, emergencies, large-scale events, etc.) of the metro, it is a considerably real issue on how to control passenger flow density and improve operational efficiency synchronously under the control requirements of specific the load factor. This paper aims to propose an integrated optimization approach for jointly researching passenger flow control and train scheduling with skip-stop patterns. Besides, the passenger dynamic demand and train occupancy rate are considered. A mixed integer programming model is formulated to minimize the unused capacity of trains and the total number of waiting passengers at platforms and outside stations. Through the comprehensive analysis of the relationship between passengers and trains, the numerical experiments are implemented in Beijing Metro Line 1 to illustrate the validity of the proposed method. Finally, discussion and comparison of the performance of integration optimization strategies with diverse scenarios are given. The results show that, under the optimized combination strategy, the average boarding rate of all stations can increase from 88.09% to 94.69% by the proposed approach, the number of waiting behaviors of passengers can be declined by 92.65%, and the average travel time of passengers can be reduced by 7.22%.