交通运输工程与信息学报2026，Vol.24Issue(2)：11-21,11.DOI:10.19961/j.cnki.1672-4747.2024.12.017
低出行密度下的通道型响应式公交路径优化
Channel-based responsive bus route optimization under low travel density
摘要
Abstract
[Background]The phenomenon of"separation of work and residence"caused by the de-velopment of urban suburbanization has intensified the operational burden and service supply diffi-culty of public transit in low-density areas.[Objective]Therefore,a design method for public trans-portation service areas based on the distribution characteristics of residents'travel is proposed,and a responsive public transportation path optimization model is further constructed to improve the inten-sive operation level and economic benefits of the public transportation system.[Method]Firstly,a channel service area design model based on travel density was constructed to determine the width of the public transportation service area;Then,with the goal of minimizing the total system cost,a chan-nel-based responsive bus route optimization model with time windows and simultaneous passenger pick-up and drop-off constraints was constructed,and an improved artificial bee colony algorithm was designed for targeted solution.[Data]Based on the OD data of passenger flow in Lufeng City,it is found that under the phenomenon of"separation of work and residence"in small and medium-sized cities,passenger flow has the characteristic of"channel travel",which provides data support for problem analysis and model training.[Conclusion]Compared with the traditional responsive bus model,it is found that in low travel density areas of small and medium-sized cities,the channel based responsive public transportation path optimization model can reduce comprehensive costs by 43.0%,save passenger travel time by 39.8%,and significantly improve the economic benefits and service quality of public transportation.关键词
城市交通/响应式公交/公交路径优化/人工蜂群算法Key words
urban traffic/responsive bus/optimization of bus routes/artificial bee colony分类
交通工程引用本文复制引用
邓钦原,秦雅琴,钱正富..低出行密度下的通道型响应式公交路径优化[J].交通运输工程与信息学报,2026,24(2):11-21,11.基金项目
国家自然科学基金项目(71861016) （71861016）
