For the purpose of traffic control a piecewiseaffine (PWA) approximation of the METANET model is proposed and tested in a model-based predictive control (MPC) framework. This approximation is provided as an alternative to the rather intensive computations when using the original nonlinear nonconvex METANET traffic flow model extended with a model for vehicular emissions and fuel consumption in ...

This paper employs previously developed modeling, validation, and stimulation tools to address, for the first time, the realistic macroscopic simulation of a real large-scale motorway network. More specifically, the macroscopic simulator METANET, involving a second-order traffic flow model as well as network-relevant extensions, is utilized. A rigorous quantitative validation procedure is appli...

We develop a macroscopic model for mixed urban and freeway traffic networks that is particularly suited for control purposes. In particular, we use an extended version of the METANET traffic flow model to describe the evolution of the traffic flows in the freeway part of the network. For the urban network we propose a new model that is based on the Kashani model. Furthermore, we also describe t...

system which is shown to be noetherian and confluent. The metanet is correct, in the sense that terms built of operations and individuals from the domain of semantic networks,i.e. describing networks can be reduced into an equivalent minimal genera­ ting expression which is not further reduc­ ible and which contains only constructors. II SPECIFICATION OF A METANET Because of the abstraction fro...

This paper describes a system that makes use of a repository of formalized frames and metaphors to automatically detect, categorize, and analyze expressions of metaphor in corpora. The output of this system can be used as a basis for making further refinements to the system, as well as supporting deep semantic analysis of metaphor expressions in corpora. This in turn provides a way to ground an...

We now apply the model predictive control (MPC) of speed limits that we have presented in previous publications [1], [2] to a calibrated METANET model of a 19 km stretch of the real-world freeway A1 in The Netherlands. This freeway regularly suffers from shock waves originating mainly from onramps, and speed limits are now used to suppress these shock waves. First, we calibrate and validate the...

Training a modern deep neural network on massive labeled samples is the main paradigm in solving scene classification problem for remote sensing, but learning from only few data points remains challenge. Existing methods few-shot sensing are performed sample-level manner, resulting easy overfitting of learned features to individual and inadequate generalization category segmentation surfaces. T...

Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...