Abstract
Existing methods of estimating section (link) density on freeways from data provided by electronic presence (loop) detectors typically require extensive knowledge or strong assumptions on prevailing flow conditions, such as homogeneity. A new data processing approach is presented which estimates density well over a wide range of traffic conditions. It does this by detecting spatially inhomogeneous traffic conditions and compensating the density estimation algorithm appropriately. The data processing algorithm is computationally simple, is not flow-level dependent, does not require any a priori knowledge of traffic conditions on the road and is insensitive to the types of uncertainty found in detector data. The algorithm uses both flow and occupancy data from adjacent detector stations to track the density on a link.