Automatic Optimization of Guidance Guardrail Layout Based on Multi-Objective Evolutionary Algorithm  

作　　者：Wei-Li Liu Yixin Chen Xiang Li Jinghui Zhong Rongjun Chen Hu Jin 

机构地区：[1]School of Computer Science,Guangdong Polytechnic Normal University,Guangzhou 510006,China [2]School of Computer Science and Engineering,South China University of Technology,Guangzhou 510006,China [3]School of Electrical Engineering,Hanyang University,Ansan 15588,Republic of Korea

出　　处：《Complex System Modeling and Simulation》2024年第4期353-367,共15页复杂系统建模与仿真(英文)

基　　金：supported in part by the National Natural Science Foundation of China under Grant 62076098;in part by the Guangdong Basic and Applied Basic Research Foundation under Grants 2021A1515110072 and 2023A1515012291;in part by the Key Research and Development Program of JiangXi Province under Grant 20212BBE53002;in part by the Key Research and Development Program of YiChun City under Grant 20211YFG4270;in part by the Special Projects in Key Fields of Ordinary Universities of Guangdong Province under Grant 2021ZDZX1087.Besides,the authors express sincere gratitude to the Transportation Operations Coordination Center(TOCC)in Chengdu for their invaluable support in conducting this research。

摘　　要：Guardrails commonly play a significant role in guiding pedestrians and managing crowd flow to prevent congestion in public places.However,existing methods of the guardrail layout mainly rely on manual design or mathematical models,which are not flexible or effective enough for crowd control in large public places.To address this limitation,this paper introduces a novel automated optimization framework for guidance guardrails based on a multi-objective evolutionary algorithm.The paper incorporates guidance signs into the guardrails and designs a coding-decoding scheme based on Gray code to enhance the flexibility of the guardrail layout.In addition to optimizing pedestrian passage efficiency and safety,the paper also considers the situation of pedestnan counterflow,making the guardrai layout more practical.Experimental results have demonstrated the effectiveness of the proposed method in alleviating safety hazards caused by potential congestion,as well as its significant improvements in passage effciency and prevention of pedestrian counte rflow.

关 键 词：automatical guardrall layout optimization crowd simulation multi-objective evolutionary algorithm 

分 类 号：U49[交通运输工程—交通运输规划与管理]