Research On Passenger Flow Control Strategy Of Urban Rail Transit Lines Considering The Impact Of COVID-19

With the rapid development of urban rail transit in China,passenger flow continues to increase,especially during peak hours,where passenger flow congestion often occurs.How to alleviate passenger flow pressure and scientifically and efficiently carry out transportation organization work has important practical significance.During the COVID-19,urban rail transit took the responsibility of COVID-19 prevention and control and ensuring passenger travel safety.Operators need to pay close attention to changes in passenger flow and strengthen COVID-19 prevention measures at all times,so as to minimize the risk of COVID-19 transmission by reducing train load ratio and passenger contact.Passenger flow control is an effective and practical method to address the above issues.Starting from the level of urban rail transit lines,this article considers two situations,namely,normal state and under the impacted of COVID-19,and focuses on the coordination and collaboration between multiple stations,to study passenger flow control strategies.This paper summarizes the current research status of passenger behavior and passenger flow characteristics,passenger flow congestion and its spread,passenger flow control strategies,and urban rail transit operations under the impact of COVID-19 at home and abroad,and conducts research on urban rail transit lines.This paper summarizes the characteristics and laws of passenger flow from two dimensions:time and space,expounds the necessity,principles,plans,specific measures,and influencing factors of passenger flow control,and introduces the regional risk classification and train load rate requirements during the COVID-19.Based on the above analysis,the scope of consideration and model assumptions for the passenger flow control issues studied in this paper are determined.The train operation process and passenger flow dynamic change process of urban rail transit system are analyzed,and relevant expressions and mathematical models are established.The model takes the optimal number of inbound passengers at each flow limiting station within each time interval as a decision variable,and takes the flow limiting intensity,equipment and facility capacity,platform capacity,total service population,and train load rate requirements during the COVID-19 as constraints.The optimization goal is to minimize the total waiting time of passengers traveling along the entire line,and the factors of passengers’ perception of time are considered in the optimization goal.An intelligent search method was chosen to solve the model.In order to improve the shortcomings of traditional algorithms,a particle swarm optimization and genetic algorithm was designed and tested using Matlab software.The results showed that the search efficiency of the designed algorithm was higher than that of a single traditional algorithm without improvement.Taking the designed simple urban rail transit system as an example,and setting the parameters of the example,the solution results show that the waiting time of passengers is significantly reduced and the phenomenon of passenger detention is eliminated,verifying the effectiveness of the model and algorithm.Determine the value range of unknown parameters in the objective function based on the actual situation of passenger time perception,repeatedly calculate the models under different values,and ultimately determine the optimal value of unknown parameters through result analysis.Taking Qingdao Metro Line 1 as an actual case,the proposed model and algorithm are applied to solve the problem by substituting relevant data.First,generate a normal passenger flow control scheme for the line,and compare the effect of the obtained passenger flow control scheme and the effect of adopting a non cooperative passenger flow control strategy(with a flow restriction rate of 20%)with those without passenger flow control.The waiting time for passengers on the entire line is reduced by 29.12%and 16.04%,respectively.The maximum number of people gathered at the platform is reduced from about 700 to about 200 and 500,respectively,This indicates that the method in this paper can effectively alleviate the contradiction between supply and demand during peak hours.Then,taking the line located in the medium risk area of the COVID-19 as the background,using the method described in this article for passenger flow control,with an appropriate increase in passenger waiting time of 14.68%,the maximum load rate of the train decreases by 37.32%,while the train load rate when operating in each section is lower than 70%,which meets the relevant requirements for COVID-19 prevention and control.This study further improves the theoretical research on passenger flow control of urban rail transit,and provides a basis for improving the efficiency of actual operation and passenger transport organization.