Comparison of Estimated Cycle Split Failures from High-Resolution Controller Event and Connected Vehicle Trajectory Data

Abstract

Current traffic signal split failure (SF) estimations derived from high-resolution controller event data rely on detector occupancy ratios and preset thresholds. The reliability of these techniques depends on the selected thresholds, detector lengths, and vehicle arrival patterns. Connected vehicle (CV) trajectory data can more definitively show when a vehicle split fails by evaluating the number of stops it experiences as it approaches an intersection, but it has limited market penetration. This paper compares cycle-by-cycle SF estimations from both high-resolution controller event data and CV trajectory data, and evaluates the effect of data aggregation on SF agreement between the two techniques. Results indicate that, in general, split failure events identified from CV data are likely to also be captured from high-resolution data, but split failure events identified from high-resolution data are less likely to be captured from CV data. This is due to the CV market penetration rate (MPR) of ~5% being too low to capture representative data for every controller cycle. However, data aggregation can increase the ratio in which CV data captures split failure events. For example, day-of-week data aggregation increased the percentage of split failures identified with high-resolution data that were also captured with CV data from 35% to 56%. It is recommended that aggregated CV data be used to estimate SF as it provides conservative and actionable results without the limitations of intersection and detector configuration. As the CV MPR increases, the accuracy of CV-based SF estimation will also improve.

Comparison at Scale of Traffic Signal Cycle Split Failure Identification from High-Resolution Controller and Connected Vehicle Trajectory Data

“…Gayen et al developed the required concepts to contrast cycle split failure estimations from HR and CV data. A preliminary analysis was carried out by comparing estimations for a single movement at a signalized intersection [37]. Even though the results provided valuable insights on estimation agreements and discrepancies, the analysis only covered a small sample, and the authors acknowledged the need to expand the study to more traffic signals with a wider distribution of traffic conditions to generate higher confidence on the derived conclusions.…”

“…Following the methodology presented by Gayen et al in [37], each movement signal cycle was assigned to one of four categories depending on whether the HR and CV techniques identify the occurrence of a split failure. In the categorization system, true (i.e., a split failure is identified) and false (i.e., a split failure is not identified) were denoted with "T" and "F" after "HR" and "CV" to indicate whether a split failure had been estimated by the respective data source.…”

“…It is important to acknowledge that there are several ways in which CV trajectories can be assigned to signal cycles. All trajectories, regardless of their number of stops, could be assigned to the ongoing cycle once they enter the detection zone [37]. Another approach that maximizes the number of cycles with allocated trajectories would be to perform a cycle assignment every time a trajectory stops after the first time.…”