Traffic Network Modeling and Extended Max-Pressure Traffic Control Strategy Based on Granular Computing Theory

Hao, Shuai; Yang, Licai

doi:10.1155/2019/2752763

Cited by 5 publications

(1 citation statement)

References 21 publications

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“…Among the few studies found, Mann [21] presented a model in which every zone was divided into subareas with the aim of reducing assignment error; Friedrich and Galster [22] suggested methods for generating connectors based on geometric features in a microscopic reference scenario; Quian and Zhang [23] proposed a connector optimization algorithm to decide the number and location of connectors in order to minimize the maximum volume/capacity ratio in a given subset of network links by changing the connector travel time; and Jafari et al [24] used a bilevel method to distribute each centroid demand both to its nearby nodes and to its peripheral nodes. Other methods for traffic network modeling are presented as in Hao and Yang [25] where they introduced the theory of granular computing to model the elements of the multilayer traffic network.…”

Section: E Network Representation a Traffic Network Is A Pairmentioning

confidence: 99%

A New Model for Locating Plate Recognition Devices to Minimize the Impact of the Uncertain Knowledge of the Routes on Traffic Estimation Results

Sánchez-Cambronero

Álvarez-Bazo

Rivas

et al. 2020

Journal of Advanced Transportation

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A number of research papers have recently shown that the use of techniques based on the installation of vehicle identification devices allows us to address the observability problem of a traffic network in a much more efficient way than if it were done with traditional techniques. The use of such devices can lead to a better data set in terms of flows and therefore to a better definition of traffic flows, which is essential for traffic management in cities and regions. However, the current methodologies aimed at network modeling and data processing which are not fully adapted to the use of these devices in obtaining the necessary data for analyzing traffic and making network forecasts. This is because the essential variable in models which used data from plate scanning (as a particular case of AVI sensors) is composed of the route flows, while traditional methods are based on the observation of link and/or origin-destination flows. In this context, this paper proposes several practical contributions, in particular: (1) a traffic network design method aimed to use the plate scanning data to estimate traffic flows and (2) an algorithm for locating plate reader devices to reduce the effect of the uncertain knowledge of route enumeration. Next, using the well-known Nguyen-Dupuis network, a sensitivity analysis has been carried out to evaluate the influence of different parameters of the model on the final solution. These parameters are the considered routes, the degree of network simplification, and the available budget to install devices. Finally, the method has been applied to a real network.

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Section: E Network Representation a Traffic Network Is A Pairmentioning

confidence: 99%

A New Model for Locating Plate Recognition Devices to Minimize the Impact of the Uncertain Knowledge of the Routes on Traffic Estimation Results

Sánchez-Cambronero

Álvarez-Bazo

Rivas

et al. 2020

Journal of Advanced Transportation

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Throughput properties and optimal locations for limited deployment of Max-pressure controls

Barman

Levin

2023

Transportation Research Part C: Emerging Technologies

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Evolvement laws and stability analyses of traffic network constituted by changing ramps and main road

Wang

Zhou

Wang

et al. 2019

Int. J. Mod. Phys. B

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Proposing realistic hybrid traffic flow model is a promising and hot topic in the area of fluid mechanics and nonlinear dynamics, since they can take advantages of combining dynamical properties of each individual vehicle and macroscopic characteristics of the global system. In this paper, different from the previous work, we propose a hybrid traffic flow model considering the dynamical competition between ramps and main roads. Afterwards, the dynamical control equations of the proposed system are established. Then, by means of performing finite difference analyses, nonlinear dynamical characteristics and specific properties of the proposed system are investigated. Evolvement laws of characteristic order parameters of the proposed traffic flow system are obtained by analyzing the change of density, velocity and current in various circumstances. Moreover, matrices of partition coefficient are employed into the proposed traffic network composed of a main road and varied ramps. Additionally, linear and nonlinear stability analyses are considered in different phase spaces. Therefore, the robustness of the proposed system is tested by both linear and nonlinear dynamics. Our work will be helpful to understand mesoscopic dynamical behaviors of each individual vehicle and inner interactions between them.

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Traffic Network Modeling and Extended Max-Pressure Traffic Control Strategy Based on Granular Computing Theory

Cited by 5 publications

References 21 publications

A New Model for Locating Plate Recognition Devices to Minimize the Impact of the Uncertain Knowledge of the Routes on Traffic Estimation Results

A New Model for Locating Plate Recognition Devices to Minimize the Impact of the Uncertain Knowledge of the Routes on Traffic Estimation Results

Throughput properties and optimal locations for limited deployment of Max-pressure controls

Evolvement laws and stability analyses of traffic network constituted by changing ramps and main road

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