A novel macroscopic traffic model based on generalized optimal velocity model
Xuan-Hao Zhou, Yong-Zai Lü
Abstract
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Xuan-Hao Zhou, Yong-Zai Lü
Abstract
Open-access reader
In this paper, we adopt the coarse graining method proposed by Lee H K et al . to develop a macroscopic model from the microscopic traffic model-GOVM. The proposed model inherits the parameter p which considers the influence of next-nearest car introduced in the GOVM model. The simulation results show that the new model is strictly consistent with the former microscopic model. Using this macroscopic model, we can avoid considering the details of each traffic on the road, and build more complex models such as road network model easily in the future.
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In this paper, we adopt the coarse graining method proposed by Lee H K et al . to develop a macroscopic model from the microscopic traffic model-GOVM. The proposed model inherits the parameter p which considers the influence of next-nearest car introduced in the GOVM model. The simulation results show that the new model is strictly consistent with the former microscopic model. Using this macroscopic model, we can avoid considering the details of each traffic on the road, and build more complex models such as road network model easily in the future.
Key concepts: Traffic model, Granularity, Computer science, Microscopic traffic flow model, Statistical physics, Network model, Traffic flow (computer networking), Traffic generation model