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The selection of the appropriate traffic signal systems solution (e.g., fully actuated [free] control, pretimed control, adaptive traffic signal control, traffic responsive plan) is critical to ensuring efficient traffic operations. The success of any selected solution is largely dependent on corridor characteristics and the nature of the experienced problems on the corridor. In addition, agency capability and constraints (e.g., staffing) along with infrastructure needs (e.g., detection) are other factors that are sometimes overlooked but can be critical during the selection process. So far, researchers have proposed tools, guidelines, and recommendations typically to select a single solution (e.g., adaptive) primarily by observing only corridor operational characteristics. Such practice leaves traffic engineers without an appropriate process/tool that can evaluate whether some other traffic solutions are more appropriate for given conditions. Therefore, the objective of this study is to develop a comprehensive traffic signal systems solutions toolbox that can incorporate corridor characteristics, operational objectives, agency capabilities, and agency constraints and offer a broad range of signal control strategies as solutions. The developed toolbox relies on data that are readily available to most agencies, such as annual average daily traffic and vehicle probe data, and incorporates a range of factors related to corridor characteristics and agency capabilities and constraints. The toolbox was applied to three corridors in Pennsylvania, U.S. Results from the case studies demonstrated that the toolbox could provide the appropriate recommendations based on unique circumstances. Additionally, the recommended solutions were generally in line with the expectations of agency representatives.

Delay is one of the most important traffic signal performance measures. In coordinated networks, understanding the characteristics of vehicle arrivals is important for coordination purposes and to properly estimate delays. When observed on a cyclical basis in real-time, distinctive arrival patterns can lead to similar delays, which may go undetected by contemporary delay models. This study proposes a set of enhancements to the Incremental Queue Accumulation (IQA) delay model to overcome the limitations of current models. Additionally, this study proposes a hybrid signal performance measure that combines delay and arrival patterns to depict signal performance truthfully. The enhancements to IQA are realised through an algorithm for the identification of distinctive vehicle arrival groups based on high-resolution signal and detection data. The results demonstrate that the proposed model provides reliable delay estimates (MAPE score in range 4.3–11.2%) while reporting a number of traffic arrival characteristics that are not available from the benchmarked models.

Pedestrian signal timings are one of the major issues to be addressed when developing signal timing plans. So far, two different treatments of pedestrian timings for coordinated systems exist. The first treatment accommodates pedestrian timing within the cycle. Therefore, it requires longer cycle lengths that usually increase the total delay on the network. In contrast, the second treatment uses shorter cycle lengths sufficient to serve vehicular demand only. The problem with the latter is that the concurrent phase is usually not long enough to serve pedestrians. Thus, with every pedestrian call, a follow-up transition process occurs, affecting cycle lengths and coordination quality. This study develops two novel pedestrian timing treatments to overcome the problems of the traditional ones. Novel pedestrian treatments utilize a cycle length optimized to cover necessary times for vehicular phases, although pedestrian timings may require longer time intervals. However, when pedestrian calls occur, their minimum safety timings are accommodated within such a shorter cycle, and thus the transition process is not required. Our study evaluates the proposed and traditional pedestrian timing treatments using a corridor of five signalized intersections in West Valley City, Utah. Various experiments were conducted in a microsimulation environment VISSIM and collected results were statistically compared. Results show the promising property of the proposed treatments, as they outperformed the traditional pedestrian timing treatments. Therefore, further investigation of these pedestrian timing treatments is warranted. Future research should investigate possibilities of implementing similar treatments to fully actuated control systems on various networks and traffic conditions.

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/Cis 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, GORhas often been misinterpreted as some similar, yet different TSPM. Therefore, if only V/Cor GORare 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/Cand GOR. Also, by evaluating existing occupancy-based measures, it was found that they can be used to estimate capacity utilization, including oversaturated conditions.

Current signal retiming policies are deficient in recognizing the potential of emerging traffic datasets and simulation tools to improve signal timings. Consequently, current practice advocates the use of periodically collected (low-resolution) traffic datasets and deterministic (low-fidelity) simulation tools. When deployed in the field, such signal timings require excessive fine-tuning. The most recent trends promote the use of high-resolution data collected at 10 Hz frequency. While such an approach shows promise, the process heavily relies on specific data sets that are neither widely available nor clearly integrated into the existing signal retiming practices and procedures. Interestingly, data collected in an ongoing fashion and aggregated in several-minute bins (referred to here as medium-resolution) have not received much attention in the traditional retiming procedures. This study examines traditional signal retiming practices to provide a contextual framework for the other retiming alternatives. The authors define and classify different resolutions of various traffic data used in the signal retiming process and propose a signal retiming procedure based on widely available medium-resolution data and high-fidelity simulation modeling. The authors apply the traditional (low-resolution and low-fidelity) and a proposed (medium-resolution and high-fidelity) approach to a 28-intersection corridor in southeastern Florida. Signal timing plans developed from the proposed approach outperformed current plans from field and those plans developed in the traditional approach by reducing the average delay anywhere between 6.5 and 26%. With regard to the number of stops, changes for the traditional and proposed approaches were of much lower significance when compared with the field signal timings. The traveling speeds have been increased by 4.1%–18% by the proposed signal timings and delay was not transferred onto the neighboring streets, as was the case for plans developed by the traditional approach. Development, calibration, and validation of models within the proposed approach are more time-consuming and challenging than the modeling needs of the traditional approach. One direction of future research should address the automation of calibration and validation procedures. The other direction for future research should be related to the field evaluation of proposed signal timing plans.