Tracking and collision avoidance of virtual coupling train control system

Abstract

“Wash hands frequently, reduce aggregation, and wear masks” is an important measure for the prevention and control of the new crown pneumonia epidemic. Rail transit is the basic means of transportation to ensure the daily travel of citizens. Carriages and stations are both densely populated places. Reducing the density of carriages and platforms is an urgent problem for rail transit operations in the epidemic. Therefore, this paper proposes a method for dynamic marshalling of trains based on virtual coupling in a major epidemic situation, describes in detail the operation mode of virtual coupling trains, and establishes a marshalling planning model based on passenger flow to optimize the scheduling of virtual coupling trains to reduce passenger density at stations. Then, combined with the virus infection probability model and social force-based passenger movement model, the infection risk of the entire process of passenger subway travel under virtual coupling was analyzed. After that, Matlab was used to simulate the infection analysis under the virtual coupling system and compare it with the traditional communication based train control system. The risk of infection during the entire journey of a passenger on the subway is less than that of CBTC. Finally, according to the results of simulation analysis, effective measures can be given that can be used in conjunction with virtual coupling to reduce the risk of infection.

Keywords

• Urban rail transit
• Virtual coupling
• Dynamic scheduling
• Epidemic prevention and control
• Infection risk analysis
• Social force model