Impact of Guideline Markings on Saturation Flow Rate at Signalized Intersections

Qin, Zhengtao; Zhao, Jing; Liang, Shidong; Yao, Jiao

doi:10.1155/2019/1786373

Cited by 11 publications

(13 citation statements)

References 28 publications

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“…In general, there are two ways to alleviate traffic congestion at signalized intersections. The first one is to improve traffic capacity with unique and refined design [6,7]. The second one is to decrease delay with optimization signal control [8,9].…”

Section: Introductionmentioning

confidence: 99%

An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

et al. 2020

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An insufficient functional relationship between adjustment factors and saturation flow rate (SFR) in the U.S. Highway Capacity Manual (HCM) method increases an additional prediction bias. The error of SFR predictions can reach 8–10%. To solve this problem, this paper proposes a comprehensive adjusted method that considers the effects of interactions between factors. Based on the data from 35 through lanes in Beijing and 25 shared through and left-turn lanes in Washington, DC, the interactions between lane width and percentage of heavy vehicles and proportion of left-turning vehicles were analyzed. Two comprehensive adjustment factor models were established and tested. The mean absolute percentage error (MAPE) of model 1 (considering the interaction between lane width and percentage of heavy vehicles) was 4.89% smaller than the MAPE of Chinese National Standard method (Standard Number is GB50647) at 13.64%. The MAPE of model 2 (considering the interaction between lane width and proportion of left-turning vehicles was 33.16% smaller than the MAPE of HCM method at 14.56%. This method could improve the accuracy of SFR prediction, provide support for traffic operation measures, alleviate the traffic congestion, and improve sustainable development of cities.

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Section: Introductionmentioning

confidence: 99%

An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

et al. 2020

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“…However, this special factor is not taken into account to modify the base saturation flow rate in HCM. Qin et al [4] proposed a new adjustment factor for guideline markings. The saturation flow rate could be estimated accurately with intersection guideline markings.…”

Section: Improved Adjustment Methodsmentioning

confidence: 99%

“…At present, researchers have proposed many estimated saturation flow rate models, which are mainly divided into the following three categories. One is a type of model based on the adjustment method in HCM [4][5][6][7][8] (see Section 2). In consideration of the traffic characteristics of different areas, they revise the existing adjusted factors and add new adjusted factors to improve the original adjustment model.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Estimation of Saturation Flow Rate at Information-Rich Signalized Intersections

et al. 2020

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Intersections are the bottlenecks of the road network. The capacity of signalized intersections restricts the operation of the road network. Dynamic estimation of capacity is necessary for signalized intersections refined management. With the development of technology, more and more detectors were installed near the intersection. It had been the information-rich environment, which provided support for dynamic estimation of capacity. A dynamic estimation method for a saturation flow rate based on a neural network was developed. It would grasp the dynamic change of saturation flow rates and influencing factors. The measure data at three scenarios (through lanes, shared right-turn and through lanes, shared left-turn and through lanes) of signalized intersections in Beijing were taken as examples to validate the proposed method. Firstly, the traffic flow characteristics of the three scenarios and factors affecting the saturation flow rate were analyzed. Secondly, neural network models of the three scenarios were established. Then the hyperparameters of neural network models were determined. After training, the neural network structure and parameters were saved. Lastly, the test set data was validated by the training model. At the same time, the proposed method was compared with the Highway Capacity Manual (HCM) method and the statistical regression method. The results show that both regression models and neural network models have better accuracy than HCM models. In a simple scenario, the neural network models are not much different from the regression models. With the increase of complexity of scenarios, the advantages of neural network models are highlighted. In through-left lane and through-right lane scenarios, the estimated saturation flow rates used by the proposed method were 7.02%, 4.70%, respectively. In the complexity of traffic scenarios, the proposed method can estimate the saturation flow rate accurately and timely. The results could be used for signal control schemes optimizing and operation managing at signalized intersections subtly.

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Systematic approach to a government‐led technology roadmap for future‐ready adaptive traffic signal control systems

Balaci,

Suh

2024

Systems Engineering

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The economic impact of inefficient traffic control systems is significant owing to prolonged commute durations, and increased energy consumption. Traffic signal control systems (TSCSs) significantly influence traffic flows at intersections. Therefore, adaptive TSCSs (ATSCSs) that can adjust to traffic conditions in real‐time have been proposed as more efficient alternatives. However, the expensive implementation of these systems highlights the need for judicious investments in appropriate technologies and infrastructure. Therefore, a comprehensive technology roadmap should be built that guides the future development of traffic control and the infusion of technologies to address traffic needs. Additionally, as ATSCSs are developed and managed by local governments, the perspective of a government‐led technology roadmap is required to guide the roadmap development and implementation. Although studies have explored technology roadmaps across numerous sectors, the viewpoint of roadmap development guided by government entities is frequently neglected despite the role of these entities in shaping technological policies, underwriting research and development initiatives, and driving nationwide innovation strategies. In this study, a comprehensive framework is proposed for developing technology roadmaps tailored for systems and technologies led by governmental entities. This framework has been adapted from the Advanced Technology Roadmap Architecture (ATRA) and brought original adjustments thereby addressing the research gap. The study also presents strategic recommendations for the ATSCS implementation in South Korea, integrating systems engineering principles for a holistic approach to technological advancements. The framework can be replicated to serve as a guide for governments seeking to implement effective and efficient technology roadmaps for public infrastructure systems.

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Impact of Guideline Markings on Saturation Flow Rate at Signalized Intersections

Cited by 11 publications

References 28 publications

An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

Dynamic Estimation of Saturation Flow Rate at Information-Rich Signalized Intersections

Systematic approach to a government‐led technology roadmap for future‐ready adaptive traffic signal control systems

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