中山大学学报（自然科学版）（中英文）2024，Vol.63Issue(1)：137-144,8.DOI:10.13471/j.cnki.acta.snus.2023B053
面向车辆个体出行检测的卡口布设优化模型
Optimization model of bayonet layout for individual vehicle travel detection
摘要
Abstract
Bayonet detector can obtain fine-grained information at individual traveler level,but it is difficult to achieve full coverage of the road network.Aiming at this problem,from the perspective of missing trajectory reconstruction,the bayonet layout optimization method for individual vehicle travel detection was studied.Considering the missing situation between two adjacent bayonet detection se-quences,the methods of first reconstruction and second reconstruction of missing trajectory were pro-posed.Based on the principle of primary reconstruction,the flow capture rate and track coverage rate were created to measure the monitoring scale of road traffic information by bayonet layout scheme.Based on the principle of secondary reconstruction,the missing trajectory dispersion was created to measure the reliability of trajectory reconstruction.A bayonet layout optimization model for individual vehicle travel detection was constructed by taking traffic capture rate,trajectory coverage as con-straints,and maximizing the dispersion of missing tracks as the optimization objective of bayonet lay-out.Particle swarm optimization algorithm was used to solve the optimization model.Taking a regional road network in Haizhu,Guangzhou as an example,the new layout and the added layout were ana-lyzed respectively.The results showed that:in the new layout scene,the optimized bayonet layout scheme increased the phase flow capture rate by 6.20%,the track coverage rate by 2.76%,and the dis-persion of missing track by 139%,which obtained better results than the current scheme in terms of in-dividual vehicle travel track detection and reconstruction.In the added layout scene,the optimization solution of added 1-6 bayonets were carried out successively,and the added positions and optimization results were obtained.关键词
城市交通/卡口布设/粒子群算法(PSO)/个体出行检测/缺失轨迹离散度Key words
urban traffic/bayonet layout/particle swarm optimization(PSO)/individual travel detec-tion/dispersion of missing trajectory分类
交通工程引用本文复制引用
乔文瑛,黄敏,张小兰..面向车辆个体出行检测的卡口布设优化模型[J].中山大学学报（自然科学版）（中英文）,2024,63(1):137-144,8.基金项目
国家重点研发计划(2020YFB1600400) （2020YFB1600400）
