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Found 6 papers, 0 papers with code
Car-Following Models: A Multidisciplinary Review
Car-following (CF) algorithms are crucial components of traffic simulations and have been integrated into many production vehicles equipped with Advanced Driving Assistance Systems (ADAS).
A rigorous multi-population multi-lane hybrid traffic model and its mean-field limit for dissipation of waves via autonomous vehicles
The choice of these parameters in the lane-change mechanism is critical to modeling traffic accurately, because different parameter values can lead to drastically different traffic behaviors.
Optimization of vaccination for COVID-19 in the midst of a pandemic
During the Covid-19 pandemic a key role is played by vaccination to combat the virus.
A deep language model to predict metabolic network equilibria
We show that deep learning models, and especially architectures like the Transformer, originally intended for natural language, can be trained on randomly generated datasets to predict to very high accuracy both the qualitative and quantitative features of metabolic networks.
Limitations and Improvements of the Intelligent Driver Model (IDM)
First it is shown that, for a specific class of initial data, the vehicles' velocities become negative or even diverge to $-\infty$ in finite time, both undesirable properties for a car-following model.
Metabolic graphs, LIFE method and the modeling of drug action on Mycobacterium tuberculosis
This paper serves as a framework for designing advanced models for drug action on metabolism.
