Development and Evaluation of Performance Measures for Capacity Utilization of Traffic Signals

Abstract

Emerging high-resolution datasets allow for developing traffic signal performance measures (TSPMs) which can provide a better understanding of traffic signal operations. One of the specific objectives of signal operations is related to the measurement of capacity utilization. A fundamental measure for capacity utilization is the “degree of saturation” ( DS), and it has both volume-based and occupancy-based formulations. The former is known as “volume over capacity ratio” ( V/C), whereas the latter is known as “green occupancy ratio” ( GOR). When V/C is used to observe capacity utilization, it is not known whether the capacity is utilized from interrupted flow, free flow, or a combination of two. Similarly, the amount of time in the cycle utilized by volume (characterized with the first and last vehicle arrival time) is not revealed within V/C. On the other hand, GOR“overlooks” cases when a high number of vehicles travel without stopping or fewer vehicles depart the signal with significant startup delays and similar. In addition, because of a lack of scientific attention, GOR has often been misinterpreted as some similar, yet different TSPM. Therefore, if only V/C or GOR are used to monitor signal performance, the understanding of utilized capacity will be incomplete or misleading. This study proposes three TSPMs: “queued volume in volume to capacity ratio” ( QViV/C), “cycle utilization” ( CLU), and “volume-occupancy capacity utilization” ( VOCU) to overcome the limitations of V/C and GOR. Also, by evaluating existing occupancy-based measures, it was found that they can be used to estimate capacity utilization, including oversaturated conditions.

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

“…Previous research has focused on the development of traffic signal performance measures [4] [7] [8] [9] [10]. These performance measures allow practitioners to validate expected operations, assess demand, capacity, or progression, and quantify delay and travel time [4].…”

Fuel-Based Nash Bargaining Approach for Adaptive Signal Control in an N-Player Cooperative Game

“…It can be argued that the level of service of signalized intersections is defined based on control delay, but we focus here on stopped delay, which is a component of control delay. Previous studies (28,31) have already established that vehicles accelerating from the idling phase consume significantly more fuel than vehicles accelerating from a decelerating phase with no idling. Our focus here is on fuel consumption, and therefore the choice of stopped delay.…”

Comparison of Arrivals on Green Estimations from Vehicle Detection and Connected Vehicle Data

“…Performance measures are valuable if they can provide information that identifies challenges and improvement opportunities ( 4 – 7 ). Capacity performance measures can locate congestion problems ( 8 – 12 ) and progression performance measures give insight on how vehicles are arriving on a system ( 3 , 13 , 14 ). The previous literature has concluded that the placement and length of detection zones, in conjunction with the controller configuration, can significantly affect the accuracy of capacity and progression metrics ( 15 ).…”