Scheduling of high-speed rail traffic based on discrete-time movement model

In this paper, a new simulation approach for solving the mixed train scheduling problem on the high-speed double-track rail line is presented. Based on the discrete-time movement model, we propose control strategies for mixed train movement with different speeds on a high-speed double-track rail line, including braking strategy, priority rule, travelling strategy, and departing rule. A new detailed algorithm is also presented based on the proposed control strategies for mixed train movement. Moreover, we analyze the dynamic properties of rail traffic flow on a high-speed rail line. Using our proposed method, we can effectively simulate the mixed train schedule on a rail line. The numerical results demonstrate that an appropriate decrease of the departure interval can enhance the capacity, and a suitable increase of the distance between two adjacent stations can enhance the average speed. Meanwhile, the capacity and the average speed will be increased by appropriately enhancing the ratio of faster train number to slower train number from 1.

Modeling and Generating Realistic Background Traffic by Hybrid Approach

One of the key challenges in largescale network simulation is the huge computation demand in fine-grained traffic simulation.Apart from using high-performance computing facilities and parallelism techniques,an alternative is to replace the background traffic by simplified abstract models such as fluid flows.This paper suggests a hybrid modeling approach for background traffic,which combines ON/OFF model with TCP activities.The ON/OFF model is to characterize the application activities,and the ordinary differential equations(ODEs) based on fluid flows is to describe the TCP congestion avoidance functionality.The apparent merits of this approach are(1) to accurately capture the traffic self-similarity at source level,(2) properly reflect the network dynamics,and(3) efficiently decrease the computational complexity.The experimental results show that the approach perfectly makes a proper trade-off between accuracy and complexity in background traffic simulation.

An integrated approach for dynamic traffic routing and ramp metering using sliding mode control

The problem of designing integrated traffic control strategies for highway networks with the use of route guidance, ramp metering is considered. The highway network is simulated using a first order macroscopic model called LWR model which is a mathematical traffic flow model that formulates the relationships among traffic flow characteristics in terms of density, flow, and mean speed of the traffic stream. An integrated control algorithm is designed to solve the proposed problem, based on the inverse control technique and variable structure control（super twisting sliding mode）. Three case studies have been tested in the presence of an on-ramp at each alternate route and where there is a capacity constraint in the network. In the first case study, there is no capacity constraint at either upstream or downstream of the alternate routes and the function of the proposed algorithm is only to balance the traffic flow on the alternate routes. In the second case study, there is capacity constraint at downstream of alternate routes. The proposed algorithm aims to avoid congestion on the main road and balance the traffic flow on the alternate routes. In the last case study, there is capacity constraint at upstream of alternate routes. The objective of proposed algorithm is to avoid congestion on the main road and to balance the traffic flow on the alternate routes. The obtained results show that the proposed algorithms can establish user equilibrium between two alternate routes even when the on-ramps, located at alternate routes, have different traffic demands.