On the Distribution of Probe Traffic Volume Estimated without Trajectory Reconstruction

TL;DR

This paper derives the exact distribution of probe traffic volume estimates from sparse probe point data without needing full trajectory reconstruction, revealing multimodality and conditions for normality.

Contribution

It provides a theoretical framework for understanding the distribution of probe traffic estimates without trajectory data, including variance and optimal parameters.

Findings

Distribution can be multimodal and non-symmetric.

As probe count increases, distribution approaches normality.

A local optimal cordon length can maximize estimation accuracy.

Abstract

In recent years, passively recorded probe traffic volumes have increasingly been used to estimate traffic volumes. However, it is not always possible to count probe traffic volume in a spatial dataset when probe trajectories cannot be fully reconstructed from raw probe point location data due to sparse recording intervals, lack of pseudonyms or timestamps. As a result, the application of such probe point location data has been limited in traffic volume estimation. To relax these constraints, we present the exact distribution of the estimated probe traffic volume in a road segment based on probe point location data without trajectory reconstruction. The distribution of the estimated probe traffic volume can exhibit multimodality, without necessarily being line-symmetric with respect to the true probe traffic volume. As more probes are present, the distribution approaches a normal distribution. The conformity of the distribution was visualised through numerical simulations. Sometimes, there exists a local optimal cordon length that maximises estimation precision. The theoretical variance of estimated probe traffic volume can address heteroscedasticity in the modelling of traffic volume estimates.