Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualizations and Performance Measures Considering Multiple Origin-Destination Paths

Abstract

Emerging connected vehicle (CV) data sets have recently become commercially available that enable analysts to develop a variety of powerful performance measures without a need to deploy field infrastructure. This paper presents a several tools using CV data to evaluate the quality of signal progression. These include both performance measures for high-level analysis as well as visualizations to examine details of 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, and the tools can be applied to select O-D paths or to all O-D paths in the corridor. Results for 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 and direction, 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, and an empirical platoon progression diagram. Comparing visualizations of only end-to-end journeys on the corridor with all journeys on the corridor reveals several features that are only visible with the latter. The study demonstrates the utility of CV trajectory data for obtaining high-level details as well as drilling down into the details