返回
Transit performance assessment based on graph analytics
DOI:10.1080/23249935.2019.1596991.png)
摘要
En 中文
GPS-equipped public transit vehicles generate a massive amount of location information, yet analytical methods based on Geographic Information System and Relational Database Management Systems are limited in their ability to handle these data for transit performance assessment. Graph analytics approach appears well suited for addressing these limitations; however, existing graph data models that have been used to represent the transit network do not provide the flexibility to incorporate mobility context from Automatic Vehicle Location (AVL) feeds with the geographic context of the network. This research work presents a new graph model that accounts for the mobility and geographical contexts of transit networks yet capable of processing a large volume of AVL data feeds for transit performance assessment. The efficacy of the proposed graph model and analytics method has been demonstrated in using simple graph queries to retrieve operational-level performance indicators such as schedule adherence, bus stops and routes activity levels.
Keyword:
Transit performance
graph data model
graph metrics
graph analytics
AVL data feeds
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.1
论文数:
939
被引数:
2.2K
机构
引用论文
Exploring the network structure and nodal centrality of China's air transport network: A complex network approach探索中国航空运输网络的网络结构和节点中心性: 复杂网络方法
Performance indicators for public transit connectivity in multi-modal transportation networks多式联运网络中公共交通连通性的性能指标

