Traffic flow simulation of modified cellular automata model based on producer-consumer algorithm.

PeerJ Computer Science Pub Date : 2022-09-20 eCollection Date: 2022-01-01 DOI:10.7717/peerj-cs.1102
Xuefeng Deng, Yi Shao, Jiaxin Song, Hui Wu
{"title":"Traffic flow simulation of modified cellular automata model based on producer-consumer algorithm.","authors":"Xuefeng Deng,&nbsp;Yi Shao,&nbsp;Jiaxin Song,&nbsp;Hui Wu","doi":"10.7717/peerj-cs.1102","DOIUrl":null,"url":null,"abstract":"<p><p>With the rise of new technologies such as the Internet of Vehicles and the Internet of Things, research on the intelligent connected vehicle has become a hot topic in contemporary times. The modeling and simulation of traffic flow are mainly used to analyze the characteristics of traffic flow and study the formation and dissipation mechanism of traffic congestion to better guide the real traffic. Cellular automata are suitable for the simulation of complex giant systems. Because of the randomness and discreteness of vehicle driving, cellular automata are often used to model and analyze traffic flow. This article mainly studies the traffic flow formed by intelligent connected vehicles. Based on the traditional NaSch model, the producer-consumer algorithm is introduced to form a multi-buffer vehicle information access mode, and an improved cellular automata model with random updates is constructed. The simulation results show that the improved cellular automata model improves the traffic congestion significantly compared with the original NaSch model in the intelligent network environment, which is consistent with the actual traffic situation. Therefore, the algorithm proposed in this article can effectively simulate the traffic flow characteristics of intelligent connected vehicles, and provide a theoretical basis for solving traffic problems.</p>","PeriodicalId":503620,"journal":{"name":"PeerJ Computer Science","volume":" ","pages":"e1102"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575854/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PeerJ Computer Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.7717/peerj-cs.1102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the rise of new technologies such as the Internet of Vehicles and the Internet of Things, research on the intelligent connected vehicle has become a hot topic in contemporary times. The modeling and simulation of traffic flow are mainly used to analyze the characteristics of traffic flow and study the formation and dissipation mechanism of traffic congestion to better guide the real traffic. Cellular automata are suitable for the simulation of complex giant systems. Because of the randomness and discreteness of vehicle driving, cellular automata are often used to model and analyze traffic flow. This article mainly studies the traffic flow formed by intelligent connected vehicles. Based on the traditional NaSch model, the producer-consumer algorithm is introduced to form a multi-buffer vehicle information access mode, and an improved cellular automata model with random updates is constructed. The simulation results show that the improved cellular automata model improves the traffic congestion significantly compared with the original NaSch model in the intelligent network environment, which is consistent with the actual traffic situation. Therefore, the algorithm proposed in this article can effectively simulate the traffic flow characteristics of intelligent connected vehicles, and provide a theoretical basis for solving traffic problems.

Abstract Image

Abstract Image

Abstract Image

基于生产者-消费者算法的改进元胞自动机模型交通流仿真。
随着车联网、物联网等新技术的兴起,智能网联汽车的研究成为当代的热点。交通流建模与仿真主要用于分析交通流的特征,研究交通拥堵的形成与消散机制,更好地引导现实交通。元胞自动机适用于复杂巨系统的仿真。由于车辆行驶的随机性和离散性,元胞自动机常用于交通流的建模和分析。本文主要研究智能网联车辆形成的交通流。在传统NaSch模型的基础上,引入生产者-消费者算法,形成多缓冲区的车辆信息访问模式,构造了改进的随机更新元胞自动机模型。仿真结果表明,在智能网络环境下,改进的元胞自动机模型与原有的NaSch模型相比,显著改善了交通拥塞情况,与实际交通情况相符。因此,本文提出的算法可以有效模拟智能网联汽车的交通流特征,为解决交通问题提供理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书