Evidence map›Paper›PMID 33669034›Full record

ArticleInternational journal of environmental research and public health2021

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

Xiaohui Wu, Ren He, Meiling He

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiaohui WuSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China.
Ren HeSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China.
Meiling HeSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-2144-8520

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Air PollutantsVehicle EmissionsCarbonCitiesGame TheoryAir PollutantsCarbonVehicle Emissionscarbon emissionschaos analysisgame theorylow-carbon traffic

Identifiers

PMID33669034
PMCPMC7956532

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.