Redirigiendo al acceso original de articulo en 24 segundos...
Inicio  /  Algorithms  /  Vol: 12 Par: 10 (2019)  /  Artículo
ARTÍCULO
TITULO

Freeway Traffic Congestion Reduction and Environment Regulation via Model Predictive Control

Juan Chen    
Yuxuan Yu and Qi Guo    

Resumen

This paper proposes a model predictive control method based on dynamic multi-objective optimization algorithms (MPC_CPDMO-NSGA-II) for reducing freeway congestion and relieving environment impact simultaneously. A new dynamic multi-objective optimization algorithm based on clustering and prediction with NSGA-II (CPDMO-NSGA-II) is proposed. The proposed CPDMO-NSGA-II algorithm is used to realize on-line optimization at each control step in model predictive control. The performance indicators considered in model predictive control consists of total time spent, total travel distance, total emissions and total fuel consumption. Then TOPSIS method is adopted to select an optimal solution from Pareto front obtained from MPC_CPDMO-NSGA-II algorithm and is applied to the VISSIM environment. The control strategies are variable speed limit (VSL) and ramp metering (RM). In order to verify the performance of the proposed algorithm, the proposed algorithm is tested under the simulation environment originated from a real freeway network in Shanghai with one on-ramp. The result is compared with fixed speed limit strategy and single optimization method respectively. Simulation results show that it can effectively alleviate traffic congestion, reduce emissions and fuel consumption, as compared with fixed speed limit strategy and classical model predictive control method based on single optimization method.

 Artículos similares

       
 
Nima Hoseinzadeh, Yangsong Gu, Lee D. Han, Candace Brakewood and Phillip B. Freeze    
In traffic operations, the aim of transportation agencies and researchers is typically to reduce congestion and improve safety. To attain these goals, agencies need continuous and accurate information about the traffic situation. Level-of-Service (LOS) i... ver más
Revista: Informatics

 
Zhenbo Lu, Jingxin Xia, Man Wang, Qinghui Nie and Jishun Ou    
Short-term traffic flow forecasting is crucial for proactive traffic management and control. One key issue associated with the task is how to properly define and capture the temporal patterns of traffic flow. A feasible solution is to design a multi-regi... ver más
Revista: Applied Sciences

 
Seongkwan M. Lee, Amr A. Shokri and Abdullah I. Al-Mansour    
Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from ... ver más
Revista: Applied Sciences

 
Wang Yuan-qing, Luo Jing     Pág. 1533 - 1543
Compared with normal weather, the traffic flow characteristics changed under the condition of adverse weather, which accounted for the difference of driving behavior. The influence of freeway traffic flow characteristics caused by different rainfall inte... ver más

 
Yuqi Guo, Yangzhou Chen and Chiyuan Zhang    
In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a d... ver más
Revista: Information