Modelling and Simulation for Train Movement Control Using Car-Following Strategy

Based on optimM velocity car-following model, in this paper, we propose a new railway tramc model for describing the process of train movement control. In the proposed model, we give an improved form of the optimal velocity function V^opt, which is considered as the desired velocity function for train movement control under different control conditions. In order to test the proposed model, we simulate and analyze the trajectories of train movements, moreover, discuss the relationship curves between the train allowable velocity and the site of objective point in detail. Analysis results indicate that the proposed model can well capture some realistic futures of train movement control.

Modeling and simulation of high-speed passenger train movements in the rail line

In this paper, we propose a new formula of the real-time minimum safety headway based on the relative velocity of consecutive trains and present a dynamic model of high-speed passenger train movements in the rail line based on the proposed formula of the minimum safety headway. Moreover, we provide the control strategies of the high-speed passenger train operations based on the proposed formula of the real-time minimum safety headway and the dynamic model of highspeed passenger train movements. The simulation results demonstrate that the proposed control strategies of the passenger train operations can greatly reduce the delay propagation in the high-speed rail line when a random delay occurs.

Smoke movement in a tunnel of a running metro train on fire

Research on the distribution of smoke in tunnels is significant for the fire emergency rescue after an operating metro train catches fire. A dynamic grid technique was adopted to research the law of smoke flow diffusion inside the tunnel when the bottom of a metro train was on fire and to compare the effect of longitudinal ventilation modes on the smoke motion when the burning train stopped. Research results show that the slipstream curves around the train obtained by numerical simulation are consistent with experimental data. When the train decelerates, the smoke flow first extends to the tail of the train. With the decrease of the train's speed, the smoke flow diffuses to the head of the train. After the train stops, the slipstream around the train formed in the process of train operation plays a leading role in the smoke diffusion in the tunnel. The smoke flow quickly diffuses to the domain in front of the train. After forward mechanical ventilation is provided, the smoke flow inside the tunnel continues to diffuse downstream. When reverse mechanical ventilation operates, the smoke in front of the train flows back rapidly and diffuses to the rear of the train.