Systematic Identification of Freeway Bottlenecks

Abstract

The algorithm presented identifies bottleneck locations, the times for which each bottleneck is active, and the delay they cause. The bottlenecks are ranked in terms of their frequency of recurrence and the magnitude of their delay impact. The algorithm works with 5-min loop detector data. It uses speed difference as an indicator of bottleneck activation. The algorithm is applied to 3 months of data from 270 mi of seven freeways in San Diego. It identifies 160 locations whose bottlenecks cause 64% of the total delay on these freeways. The top 10 account for 61% of the delay from all bottlenecks. The method can be used in any area in which large amounts of data are available. Transportation authorities may use it to identify bottlenecks and to track their impact over time.