Performance Characterization of Arterial Traffic Flow with Probe Vehicle Data

Extensive literature in the adaptive control field uses local detection available from the traffic controller as input to various control models to adjust splits, cycle lengths, and offsets. All these models have implicit control objectives, which include facilitated progression, minimized stops, minimized delay, and equitable allocation of green time. Enormous opportunities exist to incorporate probe data into the decision process with respect to when and where adaptive control can be used and which operating objectives are most applicable to a corridor as well as to an outcome assessment tool to evaluate the effectiveness of adaptive control. The research reported in this paper compared how probe data sources could be used to identify appropriate adaptive control objectives and to assess the performance of adaptive systems. Four case studies demonstrated how travel time data could be used to evaluate existing conditions, to evaluate the outcome of a traditional signal retiming, and to assess the feasibility of adaptive control opportunities. Currently, the richest probe data sets are provided by agency-installed equipment. Given the increasing penetration of crowd-sourced probe data devices and the onset of connected vehicle infrastructure, however, these sources could provide similarly rich data. This paper recommends that commercial data providers begin to develop more detailed base maps. These maps would provide richer probe data information, such as hour-by-hour statistical distributions and approach delay for signalized arterials for which the segments did not span multiple intersections. This recommendation should motivate agencies to develop more detailed specifications for probe data that will better serve their needs.