A micro-action-based decision-making framework for simulating overtaking behaviors of heterogeneous pedestrians

IF 14.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Information Fusion Pub Date : 2025-01-01 DOI:10.1016/j.inffus.2024.102898
Jingxuan Peng, Zhonghua Wei, Yanyan Chen, Shaofan Wang, Yongxing Li, Liang Chen, Fujiyama Taku
{"title":"A micro-action-based decision-making framework for simulating overtaking behaviors of heterogeneous pedestrians","authors":"Jingxuan Peng, Zhonghua Wei, Yanyan Chen, Shaofan Wang, Yongxing Li, Liang Chen, Fujiyama Taku","doi":"10.1016/j.inffus.2024.102898","DOIUrl":null,"url":null,"abstract":"In many public places, the heterogeneity of pedestrians leads to diverse travel behaviors including overtaking behavior. However, according to the variety of factors such as the heterogeneous attributes of pedestrians and the alterations of surrounding environment, the previous models for simulating overtaking behavior exist the problems of behavior loss or decision imbalance. By observing that overtaking behavior can be regarded as a process consisting of multiple micro-actions, this paper proposes a micro-action-based macro-to-micro decision-making (M3DM) framework to simulate fine-grained overtaking behavior of heterogeneous pedestrians. The framework incorporates two modules: micro-action modeling (MM) and macro-to-micro decision-making (MMDM) modules. The former module constructs the mapping relationship between proposed micro-actions and multiple personality characterization, and builds the simulation model of each micro-action. While the latter module integrates the density based macro and energy consumption based micro decision into framework, which achieves a more realistic simulation of overtaking behavior. Extensive real experiments are conducted to calibrate the parameters and verify the rationality of our framework. Moreover, two different simulation cases prove the authenticity of the proposed simulation model. The results indicate that the M3DM framework can significantly enhance the simulation accuracy of pedestrian behaviors, providing valuable insights for pedestrian flow management and safety in high-density environments.","PeriodicalId":50367,"journal":{"name":"Information Fusion","volume":"74 1","pages":""},"PeriodicalIF":14.7000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Fusion","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1016/j.inffus.2024.102898","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In many public places, the heterogeneity of pedestrians leads to diverse travel behaviors including overtaking behavior. However, according to the variety of factors such as the heterogeneous attributes of pedestrians and the alterations of surrounding environment, the previous models for simulating overtaking behavior exist the problems of behavior loss or decision imbalance. By observing that overtaking behavior can be regarded as a process consisting of multiple micro-actions, this paper proposes a micro-action-based macro-to-micro decision-making (M3DM) framework to simulate fine-grained overtaking behavior of heterogeneous pedestrians. The framework incorporates two modules: micro-action modeling (MM) and macro-to-micro decision-making (MMDM) modules. The former module constructs the mapping relationship between proposed micro-actions and multiple personality characterization, and builds the simulation model of each micro-action. While the latter module integrates the density based macro and energy consumption based micro decision into framework, which achieves a more realistic simulation of overtaking behavior. Extensive real experiments are conducted to calibrate the parameters and verify the rationality of our framework. Moreover, two different simulation cases prove the authenticity of the proposed simulation model. The results indicate that the M3DM framework can significantly enhance the simulation accuracy of pedestrian behaviors, providing valuable insights for pedestrian flow management and safety in high-density environments.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
Information Fusion
Information Fusion 工程技术-计算机:理论方法
CiteScore
33.20
自引率
4.30%
发文量
161
审稿时长
7.9 months
期刊介绍: Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.
期刊最新文献
Improving the local diagnostic explanations of diabetes mellitus with the ensemble of label noise filters TCIP: Network with topology capture and incongruity perception for sarcasm detection A micro-action-based decision-making framework for simulating overtaking behaviors of heterogeneous pedestrians Images, normal maps and point clouds fusion decoder for 6D pose estimation Obfuscation-resilient detection of Android third-party libraries using multi-scale code dependency fusion
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1