Identification of recurring traffic bottlenecks using ANPR technology
Tackling traffic congestion in urban cities remains an open challenge. Recently, the increasing use of a new class of sensors, Automatic Number Plate Recognition (ANPR) cameras, provides new insights into the travelpatterns of individual vehicles and promises to significantly enhance current systems for traffic management and control. In this work we investigate whether networks of ANPR cameras can be used to identify traffic bottlenecks and assess their impact in urban road networks managed by local traffic authorities. In particular, we propose a rule-based bottleneck activation algorithm to detect time periods when a bottleneck has substantial effect on traffic flow upstream of the bottleneck. We discuss limitations of the algorithm and outline the requirements necessary to expand this approach to road networks of arbitrary size and structure.
Engineered world Policy and governance