Systematic Approach to Analyze Travel Time in Road-Based Mass Transit Systems Based on Data Mining

被引:4
|
作者
Cristobal, Teresa [1 ]
Padron, Gabino [1 ]
Quesada-Arencibia, Alexis [1 ]
Alayon, Francisco [1 ]
Garcia, Carmelo R. [1 ]
机构
[1] Univ Las Palmas Gran Canaria, Inst Cybernet, Las Palmas Gran Canaria 35017, Spain
来源
IEEE ACCESS | 2018年 / 6卷
关键词
Road-based mass transit systems; travel time; intelligent transportation systems; data mining; pattern clustering; global positioning system; BUS-ARRIVAL-TIME; PREDICTION MODEL; DEMAND; SERVICE;
D O I
10.1109/ACCESS.2018.2837498
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Road-based mass transit systems are an effective means to combat the negative impact of transport that is based on private vehicles. Providing quality of service in this type of transit system is a priority for transport authorities. In these systems, travel time (TT) is a basic factor in quality of service. This paper presents a methodology, based on data mining, for analyzing TT in a mass transit system that is planned by timetable. The objective of the methodology is to understand the behavior patterns of TTs on the different routes of the transport network, as well as the factors that influence these patterns. To achieve this objective, the methodology uses clustering techniques to process the GPS data provided by the vehicles of the public transport fleet. The results that were obtained when implementing this methodology in a public transport company are presented as a use case, demonstrating its validity.
引用
收藏
页码:32861 / 32873
页数:13
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