ArticleHeliyon2023
A multi-agent model of traffic simulation around urban scenic spots: From the perspective of tourist behaviors.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper proposes a multi-agent model to simulate the traffic around urban scenic spots within tourist cities, where a newly added tourist agent is involved. Due to the flexible nature of tour travel demand and the impact of the real-time information of mobile application on tourist behaviors, there is an interactive process between tourists' travel behaviors and traffic state around scenic spots. To validate the proposed model, a case study of the Yanwu Road section at the Qunxian Gate of Xiamen University is conducted. According to the proposed model, the influence of tourist behaviors on the traffic states can be obtained, specifically, the threshold of tourist flow that triggers changes in traffic states can be obtained. This valuable information empowers policymakers to strategically manage tourist flows and mitigate traffic congestion around scenic spots. This means that this research also provides a novel and innovative approach for traffic management demand.
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Registered trials
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.