Relative Flow Data: New Opportunities for Traffic State Estimation

Traffic state information is crucial for different applications, e.g., in design and operation of road traffic networks, and in navigation services. Traffic sensing data, e.g., loop-detector data, may directly provide the desired information. Alternatively, the traffic state information may be estimated with data that only provides partial and...

On the value of relative flow data

Traffic flow can be described using three dimensions, i.e., space x, time t and cumulative flow N. This study considers estimating the cumulative flow over space and time, i.e., N(x,t), using relative flow data collected by stationary and moving observers. Stationary observers, e.g., loop-detectors, can observe flow at fixed position over...

Macroscopic traffic state estimation using relative flows from stationary and moving observers

This article presents a procedure to estimate the macroscopic traffic state in a pre-defined space-time mesh using relative flow data collected by stationary and moving observers. The procedure consist of two consecutive and independent processes: (1) estimate point observations of the cumulative vehicle number in space-time, i.e., N(x, t),...