  Crowdsourced GPS probe data has become a major source of real-time traffic
information applications. In addition to traditional traveler advisory systems
such as dynamic message signs (DMS) and 511 systems, probe data is being used
for automatic incident detection, Integrated Corridor Management (ICM), end of
queue warning systems, and mobility-related smartphone applications. Several
private sector vendors offer minute by minute network-wide travel time and
speed probe data. The quality of such data in terms of deviation of the
reported travel time and speeds from ground-truth has been extensively studied
in recent years, and as a result concerns over the accuracy of probe data has
mostly faded away. However, the latency of probe data, defined as the lag
between the time that disturbance in traffic speed is reported in the
outsourced data feed, and the time that the traffic is perturbed, has become a
subject of interest. The extent of latency of probe data for real-time
applications is critical, so it is important to have a good understanding of
the amount of latency and its influencing factors. This paper uses high-quality
independent Bluetooth/Wi-Fi re-identification data collected on multiple
freeway segments in three different states, to measure the latency of the
vehicle probe data provided by three major vendors. The statistical
distribution of the latency and its sensitivity to speed slowdown and recovery
periods are discussed.
