Chapter
Apr 26, 2012

A Hybrid Macro-Microscopic Model for Real Time Freeway Traffic Simulation

Publication: ICTIS 2011: Multimodal Approach to Sustained Transportation System Development: Information, Technology, Implementation

Abstract

Macroscopic traffic flow models play a significant role in the Intelligent Transportation Systems (ITS), especially for the urban traffic control and the dynamic traffic assignment. Two main problems limit the application of the existing traffic models. One is the traffic dynamics described by the complex nonlinear equations which are difficult to resolve in real time, and the other is that some model parameters need to be calibrated in prior. This paper presents a hybrid macroscopic and microscopic (macro-microscopic) traffic flow model of freeway traffic by extending the cell transmission model (CTM) with the real time speed dynamics. Simple supplying and demanding functions are defined to represent the traffic propagation between the upstream and downstream cell boundaries. A microscopic car-following model is integrated to specify the dynamics of the average speed in each cell. Simulation results with specific traffic data set collected from a 4-kilometre long urban freeway show the performance of the model compared to the well-known METANET model.

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Go to ICTIS 2011
ICTIS 2011: Multimodal Approach to Sustained Transportation System Development: Information, Technology, Implementation
Pages: 888 - 896

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Published online: Apr 26, 2012

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Beijing University of Technology, School of Electronic Information and Control Engineering, Chaoyang District, 100 PingLe Yuan, Beijing, 100124.E-mail: [email protected]
Li-guo Zhang [email protected]
Associate Professor, Beijing University of Technology, School of Electronic Information and Control Engineering, Chaoyang District, 100 PingLe Yuan, Beijing, 100124.E-mail: [email protected]
Yang-zhou chen [email protected]
Professor, Beijing University of Technology, School of Electronic Information and Control Engineering, Chaoyang District, 100 PingLe Yuan, Beijing, 100124.E-mail: [email protected]

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