Vehicle Route Selection Based on Game Evolution in Social Internet of Vehicles

Lin, Kai; Li, Chensi; Fortino, Giancarlo; Rodrigues, Joel J. P. C.

doi:10.1109/jiot.2018.2844215

Cited by 57 publications

(18 citation statements)

References 25 publications

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“…erefore, the game of poverty alleviation among multiple subjects arises at the historic moment. Yu et al constructed multiplayer game models based on game theory and analyzed how to formulate a reasonable and scientific accurate poverty alleviation system by using the optimal solution [50][51][52][53].…”

Section: Literaturementioning

confidence: 99%

Multiagent Collaborative Governance for Targeted Poverty Alleviation from the Perspective of Stakeholders

Zhang

Ming

et al. 2020

Complexity

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As a social problem involving a wide range of objects, targeted poverty alleviation governance needs to clearly define stakeholders and identify their behaviour choices, so as to seek a multiagent collaborative governance strategy, and strive to jointly promote the realization of a targeted poverty alleviation goals in an atmosphere to win-win cooperation and benefit sharing. By constructing a three-subject evolutionary game model of local government, social organization, and poverty group in the process of targeted poverty alleviation, this paper discusses the influence of their behavioural decisions on multisubject collaborative governance of targeted poverty alleviation and selects samples to carry out simulation experiments on the model. The results show that, first, superior government support has little effect on the evolution of tripartite competition, and the conclusion is inconsistent with the general cognition. However, the enhancement of support from local governments and social organizations can effectively promote the transformation of the willingness of the poor groups to cooperate. Second, a modest increase in the punishment of social organizations and poor groups can have a binding effect on the behavioural strategy choices of both sides and ultimately promote the process of targeted poverty alleviation. Third, the increase in the benefits of social organizations and poor groups can significantly improve the willingness of both sides to cooperate, so the “endogenous driving force” of the poor groups should be enhanced to achieve the Pareto optimal state of targeted poverty alleviation.

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Section: Literaturementioning

confidence: 99%

Multiagent Collaborative Governance for Targeted Poverty Alleviation from the Perspective of Stakeholders

Zhang

Ming

et al. 2020

Complexity

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“…Internet of Things (IoT). The vehicle localization is becoming more and more important for Internet of Vehicles (IoV) [3], [4] since the data transmission is based on accurate location information of vehicles. Generally, vehicle localization can be accurately achieved by the cooperation between Global Positioning Systems (GPS) and motion sensors on the vehicles in most scenarios when the GPS is available [5].…”

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confidence: 99%

Assistant Vehicle Localization Based on Three Collaborative Base Stations via SBL-Based Robust DOA Estimation

Wang

Wan

Dong

et al. 2019

IEEE Internet Things J.

185

101

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As a promising research area in Internet of Things (IoT), Internet of Vehicles (IoV) has attracted much attention in wireless communication and network. In general, vehicle localization can be achieved by the Global Positioning Systems (GPS). However, in some special scenarios, such as cloud cover, tunnels or some places where the GPS signals are weak, GPS cannot perform well. The continuous and accurate localization services cannot be guaranteed. In order to improve the accuracy of vehicle localization, an assistant vehicle localization method based on Direction-of-Arrival (DOA) estimation is proposed in this paper. The assistant vehicle localization system is composed of three Base Stations (BS) equipped with a Multiple Input Multiple Output (MIMO) array. The locations of vehicles can be estimated if the positions of the three BSs and the DOAs of vehicles estimated by the BSs are known. However, the DOA estimated accuracy maybe degrade dramatically when the electromagnetic environment is complex. In the proposed method, a Sparse Bayesian Learning (SBL) based robust DOA estimation approach is first proposed to achieve the off-grid DOA estimation of the target vehicles under the condition of non-uniform noise, where the covariance matrix of non-uniform noise is estimated by a Least Squares (LS) procedure, and a grid refinement procedure implemented by finding the roots of a polynomial is performed to refine the grid points to reduce the off-grid error. Then, according to the DOA estimation results, the target vehicle is cross-located once by each two BSs in the localization system. Finally, robust localization can be realized based on the results of three-time cross-location. Plenty of simulation results demonstrate the effectiveness and superiority of the proposed method.

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“…Smart community governance makes reasonable use of the Internet platform to enrich the multiple experiences of community residents in smart living and joy in the community XI [9]. Sookhak et al pointed out that the construction of smart communities covers the daily needs of residents such as government, medical care, and education, and the wisdom facilities link the daily lives of residents, gradually replacing the traditional fixed work and study mode and effectively driving the residents' life [10]. e intelligent facilities will gradually replace the traditional fixed working and learning mode and effectively lead to the change of residents' lifestyle.…”

Section: Related Studiesmentioning

confidence: 99%

Game Analysis of Dynamic Planning Evolution for the Optimization of Community Governance Structure in Smart Cities

Liang

2021

Complexity

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In this paper, we study the structural optimization of community governance in smart cities and optimize the structure based on the game analysis of dynamic planning evolution. Theoretically, the connotation and extension of the concept of “self-organization” are cleared, and the environment and conditions of community self-organization formation, the formation process of community self-organization, and the types of community self-organization are discussed. The so-called “self-organization” is a process of spontaneously moving from disorder to order, and the environment and conditions of community self-organization are mainly the openness, nonequilibrium state, and nonlinearity of the system. The key parameters of the contract with the change of the values of each factor make up for the inability to collect data for the empirical study in this paper; then, it presents four linear stages along with the cause such as self-creation, self-expansion, self-maintenance, and self-degeneration, respectively. The types of community self-organization mainly include community self-organization with random aggregation, socialized community self-organization, and stable community self-organization with autonomy orientation. By systematically sorting out the relationship between community self-organization and government, while confirming the positive significance of community self-organization to community cultural governance, various complex conflicts and game relationships will deeply affect the actual effectiveness of cultural governance and provide useful knowledge reference for future community cultural governance.

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Vehicle Route Selection Based on Game Evolution in Social Internet of Vehicles

Cited by 57 publications

References 25 publications

Multiagent Collaborative Governance for Targeted Poverty Alleviation from the Perspective of Stakeholders

Multiagent Collaborative Governance for Targeted Poverty Alleviation from the Perspective of Stakeholders

Assistant Vehicle Localization Based on Three Collaborative Base Stations via SBL-Based Robust DOA Estimation

Game Analysis of Dynamic Planning Evolution for the Optimization of Community Governance Structure in Smart Cities

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