Transit (satellite)

Algorithm

Control (management)

Discretization

Engineering

Transport engineering

Traffic flow (computer networking)

Public transport

China

Beijing

Computer science

Integer programming

Computer network

Urban rail transit

Operations research

Mathematics

Rail transit

Flow (mathematics)

Political science

Flow control (data)

Automotive engineering

Mathematical analysis

Artificial intelligence

Geometry

Traffic congestion

Light rail transit

Applied Mathematical Modelling

Urban rail traffic congestion is becoming increasingly serious due to the large traffic demands in modern cities. In order to ensure the safety and quality of station services in peak hours, it's necessary to adopt some reasonable and effective passenger flow control strategies. In this study, through considering the time-dependent passenger demands, a passenger flow control model based on the network-level system is explicitly developed. The passenger successive motion process is discretized by the modeling method. Systematically considering the coordinated relationship between traffic demands and strict capacity constraints (including station passing capacity, platform load capacity and train transport capacity), we establish a mixed integer linear programming model to minimize the total passenger waiting time (including passengers outside stations and on the platforms). The optimization software Cplex is adopted to solve the developed model, and a real network of Beijing urban railway is calibrated to verify the effectiveness of the suggested model. As a result, the proposed flow control strategies can provide detailed information about control stations, control durations and control intensities, and can effectively reduce the total waiting time and relieve the number of stranded passengers in the urban rail transit network.

Passenger flow control strategies for urban rail transit networks