scholarly journals Level-of-Service Based Hierarchical Feedback Control Method of Network-Wide Pedestrian Flow

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Zhe Zhang ◽  
Limin Jia ◽  
Yong Qin
Keyword(s):  
Feedback Control ◽  
Flow Control ◽  
Network Flow ◽  
Control Method ◽  
Control Model ◽  
Transmission Model ◽  
Level Of Service ◽  
Cell Transmission Model ◽  
Pedestrian Flow ◽  
Link Density

Pedestrian flow control is usually used to manage the crowd motion in public facilities to avoid congestion. We propose a network-wide pedestrian flow model based on the modified cell transmission model which describes the link flow as ordinary differential equations. The network flow control model (NFCM) is proposed to limit the number of pedestrians in a network according to the level-of-service requirements; however, the NFCM cannot ensure the uniform link density which is a premise of using NFCM. As a solution, the link flow control model (LFCM) is proposed to adjust the walking speed of pedestrians to realize the uniform link density. The NFCM provides the inputs for the LFCM and the LFCM compensates the deficiency of NFCM. Both NFCM and LFCM control the pedestrian flow in a cooperative way, and thus they form the hierarchical feedback control model (HFCM) of network-wide pedestrian flow. At last, the proposed HFCM is applied to control the crowd of a hall and the comparison of the simulation results in the controlled and uncontrolled scenarios shows that the proposed HFCM has the capability to suggest the optimal link inflows and walking speeds in real time to meet the LOS requirement.

Novel Network Flow Control Model on Multi-Team Game Theory

2010 ◽  
Vol 32 (2) ◽  
pp. 267-271 ◽  
Author(s):  
Hui-bin Feng ◽  
Shun-yi Zhang ◽  
Chao Liu ◽  
Jue-fu Liu
Keyword(s):  
Game Theory ◽  
Flow Control ◽  
Network Flow ◽  
Control Model ◽  
Team Game

Intelligent control of complex traffic conditions based on machine learning

2021 ◽  
pp. 1-12
Author(s):  
Zhe Li
Keyword(s):  
Machine Learning ◽  
Simulation Model ◽  
Traffic Simulation ◽  
Learning Algorithms ◽  
Control Model ◽  
Machine Learning Algorithms ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Conditions ◽  
Simulation Control

 In order to improve the simulation effect of complex traffic conditions, based on machine learning algorithms, this paper builds a simulation model. Starting from the macroscopic traffic flow LWR theory, this paper introduces the process of establishing the original CTM mathematical model, and combines it with machine learning algorithms to improve it, and establishes the variable cell transmission model VCTM ordinary transmission, split transmission, and combined transmission mathematical expressions. Moreover, this paper establishes a road network simulation model to calibrate related simulation parameters. In addition, this paper combines the actual needs of complex traffic conditions analysis to construct a complex traffic simulation control model based on machine learning, and designs a hybrid microscopic traffic simulation system architecture to simulate all relevant factors of complex road conditions. Finally, this paper designs experiments to verify the performance of the simulation model. The research results show that the simulation control model of complex traffic conditions constructed in this paper has certain practical effects.

scholarly journals A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yuankai Huang ◽  
Qicai Zhou ◽  
Xiaolei Xiong ◽  
Jiong Zhao
Keyword(s):  
Model Predictive Control ◽  
Flow Control ◽  
Real Time ◽  
Predictive Control ◽  
Dynamic Optimization ◽  
Network Flow ◽  
Control Method ◽  
Discrete Event ◽  
Transport Systems ◽  
Intermodal Transport

With the development of information technology, intermodal transport research pays more attention to dynamic optimization and multi-role cooperation. The core issue of this paper was to realize container routing with dynamic adjustment, real-time optimization, and multi-role cooperation characteristics in the intermodal transport network. This paper first introduces the Intermodal Transport Cooperation Protocol (ITCP) that describes the operation and analysis of intermodal transport systems with the concept of encapsulation and layering. Then, a new network flow control method was built based on Model Predictive Control (MPC) in the ITCP framework. The method takes real-time information from all ITCP layers as input and generates flow control decisions for containers. To evaluate the method’s effectiveness, a discrete event simulation experiment is applied. The results show that the proposed method outperforms the all-or-nothing method in scenarios with high freight volume, which means the method proposed in this paper can effectively balance the network transport load and reduce network operating costs. The research of this paper may throw some new light on intermodal transport research from the perspectives of digitization, multi-role cooperation, dynamic optimization, and system standardization.

Freeway Ramp Metering Based on Cell Transmission Model and Fuzzy Control

2013 ◽  
Vol 448-453 ◽  
pp. 3553-3556
Author(s):  
Qian Jin Shi ◽  
Yan Yan Liu ◽  
Xin Rong Liang ◽  
Chao Jun Dong
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Ramp Metering ◽  
Transmission Model ◽  
Rule Base ◽  
Cell Transmission Model ◽  
Nonlinear Feedback ◽  
Flow Process ◽  
Fuzzy Variables ◽  
Cell Transmission

Aiming at the nonlinear and time variant characteristics of a ramp control system, a fuzzy control method is applied to freeway ramp metering in this paper. A cell transmission model (CTM) to describe the freeway flow process is firstly established. Based on the model and in conjunction with nonlinear feedback theory, fuzzy control based ramp controllers are then designed. The ramp metering rates are determined by fuzzy control according to density tracking errors and error increments. Triangle curves are used for the membership functions of the fuzzy variables. The rule base including 56 fuzzy rules is also established. Finally, the controllers are simulated in MATLAB software. The results show that this method can achieve a perfect density tracking performance and eliminate traffic congestion. This approach is quite effective to freeway ramp metering.

Sign in / Sign up

Export Citation Format

Share Document