TITLE:
Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualization and Performance Measurement
AUTHORS:
Shoaib Mahmud, Christopher M. Day
KEYWORDS:
Traffic Signal Performance Measures, Vehicle Trajectory Data, Connected Vehicle Data
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.13 No.3,
June
2,
2023
ABSTRACT: Emerging connected vehicle (CV) data sets have recently become
commercially available, enabling analysts to develop a variety of powerful
performance measures without deploying any field infrastructure. This paper
presents several tools using CV data to evaluate traffic progression quality
along a signalized corridor. These include both performance measures for
high-level analysis as well as visualizations to examine details of the coordinated
operation. With the use of CV data, it is possible to assess not only the
movement of traffic on the corridor but also to consider its origin-destination
(O-D) path through the corridor. Results for the real-world operation of an
eight-intersection signalized arterial are presented. A series of high-level performance measures are used
to evaluate overall performance by time of day, with differing results by
metric. Next, the details of the operation are examined with the use of two
visualization tools: a cyclic time-space diagram (TSD) and an empirical platoon
progression diagram (PPD). Comparing
flow visualizations developed with different included O-D paths reveals several
features, such as the presence of secondary and tertiary platoons on certain sections
that cannot be seen when only end-to-end journeys are included. In addition,
speed heat maps are generated, providing both speed performance along the
corridor and locations and the extent of the queue. The proposed visualization
tools portray the corridor’s performance holistically instead of combining individual signal
performance metrics. The techniques exhibited in this study are compelling for
identifying locations where engineering solutions such as access management or
timing plan change are required. The recent progress in infrastructure-free
sensing technology has significantly increased the scope of CV data-based
traffic management systems, enhancing the significance of this study. The study demonstrates the utility of CV trajectory data
for obtaining high-level details of the corridor performance as well as
drilling down into the minute specifics.