Long Short-Term Memory Network Based Trajectory Prediction Incorporating Air Traffic Dynamics

Accurate 4D trajectory predictions are required for the implementation of Trajectory Based Operations. In addition, decentralized, free routing can make medium- to long-term flight trajectories more difficult to predict. Novel trajectory prediction techniques are needed, independent of waypoint-to-waypoint navigation and air traffic control...

Multiscale Pattern Recognition of Transport Network Dynamics and its Applications: A bird’s eye view on transport

Cities are complex, dynamic and ever-evolving. We need to understand how these cities work in order to predict, control or optimize their operations. We have identified some open issues related to network and data complexity that need to be solved to build feasible methods for these purposes. To this end, we first build multiscale graphs...

A compact and scalable representation of network traffic dynamics using shapes and its applications

The biggest challenge of analysing network traffic dynamics of large-scale networks is its complexity and pattern interpretability. In this work, we present a new computationally efficient method, inspired by human vision, to reduce the dimensions of a large-scale network and describe the traffic conditions with a compact, scalable and...

Empirical MFDs using Google Traffic Data

<br/>The Macroscopic Fundamental Diagram (MFD) describes the relation between accumulation and speed in a zone. While theoretically expected, empirical validations have been done with limited numbers of floating car (e.g., taxi) data, and loop detectors. This paper will verify existence, shape and crispness of the MFD using Floating Car Data ...

An Area-Aggregated Dynamic Traffic Simulation Model

Microscopic and macroscopic dynamic traffic models not fast enough to run in an optimization loop to coordinate traffic measures over areas of twice a trip length (50x50 km). Moreover, in strategic planning there are models with a spatial high level of detail, but lacking the features of traffic dynamics. This paper introduces the Network...

Traffic dynamics: Its impact on the macroscopic fundamental diagram

Literature shows that–under specific conditions–the Macroscopic Fundamental Diagram (MFD) describes a crisp relationship between the average flow (production) and the average density in an entire network. The limiting condition is that traffic conditions must be homogeneous over the whole network. Recent works describe hysteresis effects:...

Macroscopic Traffic Dynamics with Heterogeneous Route Patterns

This paper investigates at an aggregated (macroscopic) scale the effects of route patterns on a road network. Four main variables are considered: the production, the mean speed, the outflow and the mean travel distance. First, a simple network with heterogeneous travel distances between origins and destinationsis studied by simulation. It...