Shortest Processing Time Scheduling to Reduce Traffic Congestion in Dense Urban Areas

Ahmad, Fawad; Mahmud, Sahibzada Ali; Yousaf, Faqir Zarrar

doi:10.1109/tsmc.2016.2521838

Cited by 49 publications

(17 citation statements)

References 34 publications

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“…The range of operations related to green technology consist of easy tasks that anybody can do at home, and result in highly qualified systems [11]. Modeling a greenhouse system generally entails an efficient technique to establish the parameters of a greenhouse microclimate physical model [12], as they often lack minor factors of influence, depending on the real greenhouse situation, which can cause errors or extreme weather conditions [13]. As for the experimental model, several variables must be tracked to properly estimate the related parameters [13].…”

Section: Green Technology Innovation and Ecological Efficiencymentioning

confidence: 99%

“…Modeling a greenhouse system generally entails an efficient technique to establish the parameters of a greenhouse microclimate physical model [12], as they often lack minor factors of influence, depending on the real greenhouse situation, which can cause errors or extreme weather conditions [13]. As for the experimental model, several variables must be tracked to properly estimate the related parameters [13]. The test results of the simulation show that the environmental variables of solar greenhouses [14,15] are forecast according to existing models, which means that current greenhouse microclimate models cannot be directly used to avoid the greenhouse system [16].…”

Section: Green Technology Innovation and Ecological Efficiencymentioning

confidence: 99%

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An Empirical Analysis of Green Technology Innovation and Ecological Efficiency Based on a Greenhouse Evolutionary Ventilation Algorithm Fuzzy-Model

et al. 2020

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The combination and convergence of energy-intensive industries developed by ecological factors based on energy clusters is discussed in this paper. Here, a few models for the prediction of greenhouse effects are used as a single type of modeling. In this model, the solar panel system is included as a measure of the greenhouse effect; Commitment Unit (CU) formulations are changed with flouted logic because solar integrations and other unknown variables are intermittent. In general, the greenhouse model with natural ventilation temperature prediction is incomplete, in which the resulting fluid logical CU problem can be solved with an evolutionary algorithm based on the definition and the theory of quantum calculation. This paper proposes a Fuzzy Model-Based Quantum Greenhouse Evolutionary Ventilation Algorithm (FM-BSQGEVA) which helps to minimize the CU problem. The QGEVA is updated to include a hierarchy-group-oriented scheme to tackle the non-linear nature of the issue and its multifaceted nature. The QGEVA is further developed to support a new binary differential operator and several genetic algorithm operators with a redefined rotational angle look-up. The chances that such operators are used on separate solutions are affected by stating the membership function based on their related fitness. The fitness function is calculated through a combination of the penalty function, objective function and the added fluid function. The models built can be used to regulate and control natural ventilation in greenhouse effects. This finding shows that an energy-intensive industrial cluster’s environmental chain of the industry has improved eco-efficiency.

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Section: Green Technology Innovation and Ecological Efficiencymentioning

confidence: 99%

Section: Green Technology Innovation and Ecological Efficiencymentioning

confidence: 99%

An Empirical Analysis of Green Technology Innovation and Ecological Efficiency Based on a Greenhouse Evolutionary Ventilation Algorithm Fuzzy-Model

et al. 2020

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“…T RAFFIC congestion has become a serious problem on the agenda of many public/private stakeholders, due to the constantly increasing urban traffic volumes, and to the lack of space and public funds to construct new transportation infrastructure. These problems are coupled with the complexity of understanding, modelling and controlling the dynamics of traffic networks [1], [2], [3]. In fact, as an indispensable part of any traffic control department, traffic signal operations play an important role in the effective functioning of urban traffic.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, as an indispensable part of any traffic control department, traffic signal operations play an important role in the effective functioning of urban traffic. A significant traffic engineering challenge is to find more intelligent traffic signalling methods to make transportation more efficient [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

A Switching-Based Adaptive Dynamic Programming Method to Optimal Traffic Signaling

Liu

Baldi

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

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The work presented in this paper concerns a switching-based control formulation for multi-intersection and multi-phase traffic light systems. A macroscopic traffic flow modelling approach is first presented, which is instrumental to the development of a model-based and switching-based optimization method for traffic signal operation, in the framework of Adaptive Dynamic Programming (ADP). The main advantage of the switching-based formulation is its capability to determine both 'when' to switch and 'which' mode to switch on without the need to use the cycle-based average flow approximation typical of state-of-the-art formulations. In addition, the framework can handle different cycle times across intersections without the need for synchronization constraints and, moreover, minimum dwell-time constraints can be directly enforced to comply with minimum green/red times in each phase. Simulation experiments on a multi-intersection and multi-phase traffic light systems are presented to show the effectiveness of the method.

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“…The large capital consumption may impair environmental protection projects and environmental supervision, thereby resulting in deterioration of air quality in the long run. Ahmad believes that the increase in urban transportation investment is not a feasible plan to reduce emissions, because upgrading existing road facilities will take a lot of time and will lead to more traffic congestion [19]. The conclusion on the relationship between transportation infrastructure and air pollution is still controversial.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Urban Transportation Infrastructure on Air Quality

et al. 2020

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While previous study has confirmed significant correlation between infrastructure construction and air quality, little is known about the nature of the relationship. In this paper, we intend to fill this gap by using the Panel Smooth Transition Regression (PSTR) model to discuss the nonlinear relationship between transportation infrastructure construction and air quality. The panel data includes 280 cities in China for the period 2000-2017. We find that the transportation infrastructure investment is positively correlated to the air quality when the GDP per capita is below RMB 7151 or the number of motor vehicle population per capita is below 37 (vehicles per 10,000 persons) where the model is in the lower regime, and that the transportation infrastructure investment is negatively correlated to the air quality when the GDP per capita is greater than RMB 7151 or the number of motor vehicle population per capita is larger than 37 (vehicles per 10,000 persons) where the model is in the upper regime. The empirical results of the three sub-samples, including eastern, western and central regions, are similar to that of the national level. Furthermore, increasing transportation infrastructure investment is conducive to improving air quality. Urban bus services, green area, population density, wind speed and rainfall are also conducive to reducing air pollution, but the role of environmental regulation is not significant. After adding the instrumental variable (urban built-up area), the conclusions are further supported. Finally, relevant policy recommendations for reducing air pollution are proposed based on the empirical results.

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Shortest Processing Time Scheduling to Reduce Traffic Congestion in Dense Urban Areas

Cited by 49 publications

References 34 publications

An Empirical Analysis of Green Technology Innovation and Ecological Efficiency Based on a Greenhouse Evolutionary Ventilation Algorithm Fuzzy-Model

An Empirical Analysis of Green Technology Innovation and Ecological Efficiency Based on a Greenhouse Evolutionary Ventilation Algorithm Fuzzy-Model

A Switching-Based Adaptive Dynamic Programming Method to Optimal Traffic Signaling

The Impact of Urban Transportation Infrastructure on Air Quality

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