A traffic model for velocity data assimilation

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Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction (2021, methodology): “Different from EKFs, the ensemble KFs was developed by Lighthill Whitham Richards (LWR) [10], [11] and was used for freeway network estimation problems [12], [13].”
Understanding Road Usage Patterns in Urban Areas (2012, methodology): “is because the amount of probe data is still too low to be used for inference of traffic volumes. Probe data has successfully been used to compute travel times and speeds along freeways and arterials (20). Thus, the validation process used to assess the accuracy of our method will rely on travel Est”
Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments (2017, background): “Advancements in traffic state estimation [21, 22, 23] have facilitated high resolution traffic monitoring, through the advent of GPS smartphone sensors [24, 25, 26, 27] that are part of the flow—termed Lagrangian or mobile sensors.”
Traffic state estimation on highway: A comprehensive survey (2017, background): “Figure 11: Disaggregated and aggregated data from GPS probe vehicles (adapted from Work et al. (2010)).”