Literature DB >> 33669034

Chaos Analysis of Urban Low-Carbon Traffic Based on Game Theory.

Xiaohui Wu1, Ren He1, Meiling He1.   

Abstract

Developing urban low-carbon traffic is an effective measure to reduce traffic carbon emissions, which are important parts of greenhouse gas. In order to understand the development characteristics and regular patterns of urban low-carbon traffic, we present a game model that enables us to predict the possible range of travel mode choice and the impact of low-carbon awareness. Through chaos analysis and simulation of the model, the authors come to realize that the proportions of travel mode choice can reach an equilibrium under a certain urban traffic system. This equilibrium is related to low-carbon awareness and the situation of the urban traffic system. The research we have done suggests that in small cities with undeveloped traffic systems, the most effective measure to achieve urban low-carbon traffic is to increase the comprehensive costs of high-carbon travel. However, in big cities with developed traffic systems, raising low-carbon awareness of residents can greatly increase the proportion of low-carbon travelers and improve the stability of travel mode choice. The results could provide development strategies and policy suggestions for urban low-carbon traffic and reduce the adverse impact of urban traffic emissions on public health.

Entities:  

Keywords:  carbon emissions; chaos analysis; game theory; low-carbon traffic

Mesh:

Substances:

Year:  2021        PMID: 33669034      PMCID: PMC7956532          DOI: 10.3390/ijerph18052285

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  6 in total

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2.  Road traffic state prediction based on a graph embedding recurrent neural network under the SCATS.

Authors:  Dongwei Xu; Hongwei Dai; Yongdong Wang; Peng Peng; Qi Xuan; Haifeng Guo
Journal:  Chaos       Date:  2019-10       Impact factor: 3.642

3.  A noise-immune LSTM network for short-term traffic flow forecasting.

Authors:  Lingru Cai; Mingqin Lei; Shuangyi Zhang; Yidan Yu; Teng Zhou; Jing Qin
Journal:  Chaos       Date:  2020-02       Impact factor: 3.642

4.  Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China.

Authors:  Jing Li; Kevin Lo; Meng Guo
Journal:  Int J Environ Res Public Health       Date:  2018-06-27       Impact factor: 3.390

5.  Evolutionary Games of Low-Carbon Behaviors of Construction Stakeholders under Carbon Taxes.

Authors:  Qiang Du; Yunqing Yan; Youdan Huang; Chanchan Hao; Jiao Wu
Journal:  Int J Environ Res Public Health       Date:  2021-01-09       Impact factor: 3.390

6.  Urban transportation energy and carbon dioxide emission reduction strategies.

Authors:  Yung-Hsiang Cheng; Yu-Hern Chang; I J Lu
Journal:  Appl Energy       Date:  2015-03-09       Impact factor: 9.746

  6 in total
  1 in total

1.  Editorial Statement and Research Ideas on Using Behavioral Models in Environmental Research and Public Health with Applications.

Authors:  Wing-Keung Wong
Journal:  Int J Environ Res Public Health       Date:  2022-06-10       Impact factor: 4.614

  1 in total

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