Evidence map›Paper›PMID 39124057›Full record

ArticleSensors (Basel, Switzerland)2024

The Parameter Calibration of Social Force Model for Pedestrian Flow Simulation Based on YOLOv5.

Tianle Li, Bingbing Xu, Weike Lu, Zidan Chen, Sizheng Zhang, Fanjun Xia

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Tianle LiSchool of Rail Transportation, Soochow University, Suzhou 215000, China.
Bingbing XuSchool of Rail Transportation, Soochow University, Suzhou 215000, China.
Weike LuSchool of Rail Transportation, Soochow University, Suzhou 215000, China.ORCID 0000-0003-0809-3590
Zidan ChenSchool of Rail Transportation, Soochow University, Suzhou 215000, China.
Sizheng ZhangSchool of Rail Transportation, Soochow University, Suzhou 215000, China.
Fanjun XiaSchool of Rail Transportation, Soochow University, Suzhou 215000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing importance of subways in urban public transportation systems, pedestrian flow simulation for supporting station management and risk analysis becomes more necessary. There is a need to calibrate the simulation model parameters with real-world pedestrian flow data to achieve a simulation closer to the real situation. This study presents a calibration approach based on YOLOv5 for calibrating the simulation model parameters in the social force model inserted in Anylogic. This study compared the simulation results after model calibration with real data. The results show that (1) the parameters calibrated in this paper can reproduce the characteristics of pedestrian flow in the station; (2) the calibration model not only decreases global errors but also overcomes the common phenomenon of large differences between simulation and reality.

Indexed as

optimizationparameter calibrationsocial force modelYOLOv5

Identifiers

PMID39124057
PMCPMC11314720

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.