2022
DOI: 10.1002/cav.2091
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R‐CTM: A data‐driven macroscopic simulation model for heterogeneous traffic

Abstract: There is a well-known trade-off between computational efficiency and computational accuracy in the field of traffic simulation. In this article, we propose a novel recurrent neural network based model with an integrated attention mechanism, called R-CTM, to simulate heterogeneous traffic flow with multiple types of vehicles. It can effectively extract the traffic flow patterns of spatial and temporal changes from training traffic data, which can be real-world traffic data or synthetic traffic data via microsco… Show more

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