A distributed origin–destination demand estimation approach for real-time traffic network management

2011 ◽  
Vol 34 (3) ◽  
pp. 217-230 ◽  
Author(s):  
Hamideh Etemadnia ◽  
Khaled Abdelghany
Keyword(s):  
Network Management ◽  
Real Time ◽  
Demand Estimation ◽  
Traffic Network ◽  
Real Time Traffic

Integrated Method for Online Calibration of Real-Time Traffic Network Management Systems

2015 ◽  
Vol 2528 (1) ◽  
pp. 106-115 ◽  
Author(s):  
Hossein Hashemi ◽  
Khaled Abdelghany
Keyword(s):  
Network Management ◽  
Real Time ◽  
Simulation Models ◽  
Calibration Method ◽  
Propagation Model ◽  
Traffic Network ◽  
Operational Conditions ◽  
Online Calibration ◽  
Integrated Method ◽  
Real Time Traffic

This paper presents an integrated method for online calibration of realtime traffic network simulation models. The method integrates a time-dependent demand adjustment module and a link-based traffic flow propagation model calibration module. These modules use available realtime traffic observations to minimize inconsistency between the model estimation results and real-world observations. The modules are integrated into a real-time traffic network management system that was developed for the US-75 corridor in Dallas, Texas. Results illustrate that the online calibration method is effective in enhancing the model's consistency in the different operational conditions.

Toward an Autonomic Architecture for Real-Time Traffic Network Management

2012 ◽  
Vol 16 (2) ◽  
pp. 45-59 ◽  
Author(s):  
Hamideh Etemadnia ◽  
Khaled Abdelghany ◽  
Salim Hariri
Keyword(s):  
Network Management ◽  
Real Time ◽  
Traffic Network ◽  
Real Time Traffic

scholarly journals Research on Optimized Control Model of Freeway Based on Dynamic Traffic Demand Estimation

2014 ◽  
Vol 6 ◽  
pp. 797293 ◽  
Author(s):  
Zhu Jiang ◽  
Shubin Li
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Demand Estimation ◽  
Control Model ◽  
Control Module ◽  
Traffic Demand ◽  
The Real ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Global Optimal

According to the estimation information of dynamic traffic demands, a novel optimal control model of freeway was established on the basis of the hierarchical concept. There are four control modules in this model. The OD prediction module predicts the total traffic demands in a long time and determines the upper bound of the future queuing length in advance; the global optimal control module predicts the future traffic state and establishes the coordination constraints for each ramp in the network; the traffic demand estimation module estimates the real-time traffic conditions for each ramp; the local adaptive control module regulates ramp metering rate according to the estimated information of the real-time traffic conditions and the results optimized by the global optimal control module. The simulation results show that this control system is of a good dynamic performance. It coordinates the benefits of various ramps and optimizes the overall performance of the freeway network.

Optimization of real-time traffic network assignment based on IoT data using DBN and clustering model in smart city

2020 ◽  
Vol 108 ◽  
pp. 976-986 ◽  
Author(s):  
Jiachen Yang ◽  
Yurong Han ◽  
Yafang Wang ◽  
Bin Jiang ◽  
Zhihan Lv ◽  
...  
Keyword(s):  
Real Time ◽  
Smart City ◽  
Traffic Network ◽  
Real Time Traffic ◽  
Clustering Model
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