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

Liang Shi, Liguo Zhang, Yangzhou Chen

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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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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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Available 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.

Key concepts: Cell Transmission Model, Microscopic traffic flow model, Traffic flow (computer networking), Macro, Computer science, Upstream (networking), Nonlinear system, Speed limit

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