  Origin-Destination matrix estimation is a keystone for traffic representation
and analysis. Traditionally estimated thanks to traffic counts, surveys and
socio-economic models, recent technological advances permit to rethink the
estimation problem. Road user identification technologies, such as connected
GPS, Bluetooth or Wifi detectors bring additional information, that is, for a
fraction of the users, the origin, the destination and to some extend the
itinerary taken. In the present work, this additional information is used for
the estimation of a more comprehensive traffic representation tool: the
link-origin-destination matrix. Such three-dimensional matrices extend the
concept of traditional origin-destination matrices by also giving information
on the traffic assignment. Their estimation is solved as an inverse problem
whose objective function represents a trade-off between important properties
the traffic has to satisfy. This article presents the theory and how to
implement such method on real dataset. With the case study of Brisbane City
where over 600 hundreds Bluetooth detectors have been installed it also
illustrates the opportunities such link-origin-destination matrices create for
traffic analysis.
