Paper Info
Title
MAC: Measuring the Impacts of Anomalies on Travel Time of Multiple Transportation Systems
Abstract
Urban anomalies have a large impact on passengers' travel behavior and city infrastructures, which can cause uncertainty on travel time estimation. Understanding the impact of urban anomalies on travel time is of great value for various applications such as urban planning, human mobility studies and navigation systems. Most existing studies on travel time have been focused on the total riding time between two locations on an individual transportation modality. However, passengers often take different modes of transportation, e.g., taxis, subways, buses or private vehicles, and a significant portion of the travel time is spent in the uncertain waiting. In this paper, we study the fine-grained travel time patterns in multiple transportation systems under the impact of urban anomalies. Specifically, (i) we investigate implicit components, including waiting and riding time, in multiple transportation systems; (ii) we measure the impact of real-world anomalies on travel time components; (iii) we design a learning-based model for travel time component prediction with anomalies. Different from existing studies, we implement and evaluate our measurement framework on multiple data sources including four city-scale transportation systems, which are (i) a 14-thousand taxicab network, (ii) a 13-thousand bus network, (iii) a 10-thousand private vehicle network, and (iv) an automatic fare collection system for a public transit network (i.e., subway and bus) with 5 million smart cards.
Year
DOI
Venue
2019
10.1145/3328913
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Keywords
DocType
Volume
anomalies, cyber physical systems, travel time components
Journal
3
Issue
Citations 
PageRank 
2
6
0.40
References 
Authors
0
7
Name
Order
Citations
PageRank
Zhihan Fang1517.77
Yang Yu215138.02
Shuai Wang313316.02
Boyang Fu471.09
Zixing Song560.40
Fan Zhang610110.18
Desheng Zhang735645.96