Developing Guidelines for Implementing Transit Signal Priority and Freight Signal Priority Using Simulation Modeling and a Decision Tree Algorithm

Iqbal, Shahadat; Ardalan, Taraneh; Hadi, Mohammed; Kaisar, Evangelos I.

doi:10.1177/03611981211057528

Cited by 15 publications

(8 citation statements)

References 10 publications

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“…These two sections experience a variety of traffic ATs, which helped with the development of a robust ML model to estimate AOG. The software used for this study, Vissim ( 37 ), was chosen because it is a proven and widely used tool for modeling various traffic operations ( 38 ). Actual network geometry, traffic volumes, turning percentages, and signal timing plans were carefully coded in Vissim, based on the data collected in the field.…”

Section: Methodsmentioning

confidence: 99%

Estimation of Arrivals on Green at Signalized Intersections Using Stop-Bar Video Detection

Gavric

Dobrota²,

Erdağı

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Across the world, traffic congestion is increasing with alarming rapidity. Traffic signal control effectiveness, in coordinated networks, is often investigated in relation to the type of vehicle arrivals at the signalized intersections. Recently, several transportation agencies have switched from traditional loop detectors to video detection. When video cameras are accompanied by computer vision, one can extract more information about traffic “dynamics” than by using traditional inductive loop detectors. Collecting arrival times of multiple vehicles after the first arrival at the stop-bar detector might be challenging when using inductive loop detectors (since after the first arrival, detector status is always occupied). However, emerging video detection systems allow tracking of each vehicle’s entrance time in the detection zone, departure time from the detection zone, and the type of vehicle. This information can be used to estimate vehicular arrival and departure times, which then can be fed into machine learning algorithms to estimate arrivals on green (AOG). However, such research ideas have not been documented so far. Thus, this paper presents an estimation model for AOG, which was developed using multigene genetic programming. A robust experimental dataset was collected from a highly calibrated and validated microsimulation model of an 11-intersection corridor in Chattanooga, TN. The results of the model’s performance analysis showed the high accuracy of the training-, testing-, and validation datasets. The practical benefit of this model is that it can be applied to estimate arrival types at intersections where only stop-bar video detection exists.

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Section: Methodsmentioning

confidence: 99%

Estimation of Arrivals on Green at Signalized Intersections Using Stop-Bar Video Detection

Gavric

Dobrota²,

Erdağı

et al. 2023

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

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“…The software used for this study, VISSIM ( 9 ), was chosen for its ability to communicate with field-like controller ECONOLITE’s ASC/3 ( 10 ) and to allow us to import an external controller. Another reason for utilizing VISSIM is it is a proven, widely used tool to model various traffic operations ( 15 , 16 ). Both ECONOLITE’s ASC/3 and external virtual controller DUMKA_E were used to test different pedestrian timing treatments in this study.…”

Section: Methodsmentioning

confidence: 99%

Development and Evaluation of Non-Traditional Pedestrian Timing Treatments for Coordinated Signalized Intersections

Gavric

SARAZHINSKY

Stevanovic

et al. 2022

Transportation Research Record: Journal of the Transportation R

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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.

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“…A high-fidelity Vissim microsimulation model of Broward Blvd, located in Fort Lauderdale, Florida, developed previously, was used as a testbed (42,45). The authors used PTV Vissim due to its flexibility to model various traffic operations/conditions (46)(47)(48)(49)(50)(51)(52)(53) and to generate high-resolution data (54)(55)(56). The examined 1 mi segment of Broward Blvd encompasses five consecutive signalized intersections (as shown in Figure 7), from SR 7 on the west to NW 31st Avenue on the east side.…”

Section: Methodsmentioning

confidence: 99%

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

Dobrota

Stevanovic

Mitrović³

et al. 2022

Transportation Research Record: Journal of the Transportation R

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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.

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Developing Guidelines for Implementing Transit Signal Priority and Freight Signal Priority Using Simulation Modeling and a Decision Tree Algorithm

Cited by 15 publications

References 10 publications

Estimation of Arrivals on Green at Signalized Intersections Using Stop-Bar Video Detection

Estimation of Arrivals on Green at Signalized Intersections Using Stop-Bar Video Detection

Development and Evaluation of Non-Traditional Pedestrian Timing Treatments for Coordinated Signalized Intersections

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

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