Evaluating the Performance of Coordinated Signal Timing: Comparison of Common Data Types with Automated Vehicle Location Data

Abstract

Performance measures are essential for managing transportation systems, including signalized corridors. Coordination is an essential element of signal timing, enabling reliable progression of traffic along corridors. Improved progression leads to less user delay, which leads to user cost savings and lower vehicle emissions. This paper presents a comparative study of signal coordination assessment using four different technologies. These technologies include detector-based high-resolution controller data, Bluetooth/Wi-Fi sensors, segment-based probe vehicle data, and automated vehicle location data consisting of GPS-based vehicle trajectories, representing the data anticipated from emerging connected vehicle technologies. The data were compiled for a 4.2-mi corridor in Holland, Michigan. The results show that all of the data sources were able to identify, at some level, where coordination issues existed. Detector-based controller data and GPS-based vehicle trajectory data were capable of showing greater detail, and could be used to make offset adjustments. The paper concludes by demonstrating the identification of signal coordination issues with the use of visual performance metrics incorporating automated vehicle location (AVL) trajectory data.

Platoon Priority Visualization Modeling and Optimization for Signal Coordination in the Connected Vehicle Environment

“…Compared with the existing works (2,(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22), more practical and emerged variables are covered in the proposed Bi-PCD. In addition, a new probabilistic surrogate quantification combined with an offset optimization is proposed to improve coordination performances.…”

“…However, CV-based signal coordination, with potential features such as high mobility, would offer remarkable and profound benefits over existing traditional signal coordination systems ( 1 , 7 ). As such, several CV-based coordination approaches have been proposed in recent years from both online control ( 6 , 7 , 11 ) and offline offset optimization ( 2 , 12 – 15 ) perspectives.…”

“…To overcome the issue of low CV market penetration rates, CV-based offline offset optimization has been increasingly investigated by integrating CV-like or CV-based data into coordination systems over the last decade ( 2 , 12 – 15 ). The first core component of this optimization is utilizing a coordination diagram which combines a detection event and a signal timing using fixed advanced detectors, called the Purdue coordination diagram (PCD) ( 16 , 17 ).…”

“…The second component of this optimization is to replace traditional data with obtained CV-like or CV-based data for both visual and quantitative optimizations. A few CV-based coordination methods are proposed ( 2 , 12 – 15 ). Day et al ( 2 , 12 , 13 ) presented detector-free offset optimization works, where CV-based trajectories were used to generate virtual detections.…”

Replicating Advanced Detection using Low Ping Frequency Probe Vehicle Trajectory Data to Optimize Signal Progression

“…In a study comparing common data types for corridor progression analysis, Remias et al. stacked two weeks of vehicle trajectory data at a low penetration rate and were able to identify areas of suboptimal progression ( 22 ).…”