This survey presents fundamental concepts, methods, and challenges related to knowledge discovery from urban trajectory data, including data acquisition, preprocessing, mining, and practical applications, ensuring that each stage is optimized to contribute to the overall performance of the mobility knowledge discovery process.
Abstract
Comprehending the mobility of entities in urban environments is crucial for developing and maintaining efficient and livable cities. This survey presents fundamental concepts, methods, and challenges related to knowledge discovery from urban trajectory data, including data acquisition, preprocessing, mining, and practical applications. Unlike previous studies, our survey offers a holistic and integrated view of these steps, ensuring that each stage is optimized to contribute to the overall performance of the mobility knowledge discovery process. Moreover, we identify operational and technical challenges, discussing potential future directions that can unlock new opportunities and advancements in this field.
This paper conducts extensive exploratory analysis, develops a Z-score anomaly detection method capable of capturing event-driven disruptions, and designs a regression model achieving a regional-scale MAPE around 10% in inbound-flow forecasting.
N. Bicocchi, Michele Arioli, Marco Mamei et al.· Journal of Ambient Intellige...· 0 citations
A logic-oriented analysis of urban traffic spatiotemporal data examines three temporal evolution characteristics: periodicity, trend, and abrupt change and extracts a logical framework for traffic condition prediction.
Shuohan Xu· Applied and Computational En...· 0 citations
The proposed framework for estimating travel times at both the link and route levels using sparse GPS data is implemented using Python scripting within the ArcGIS environment and validated against high-frequency GPS records, demonstrating that the approach yields accurate and reliable results despite the data sparsity.
A. Ganjkhanloo, Mojtaba Rajabi-Bahaabadi· 0 citations
Cascading urban disruptions, from routine roadworks to regional floods, affect mobility in ways that cut across employment, health services, and economic productivity. Yet no standardised methodology exists to synthesise heterogeneous disruption data across scales for sustainable city planning. This paper develops and...
Y. Rezgui, Afrouz Ghaemi, A. Ghoroghi et al.· Environment Systems and Deci...· 0 citations
A systematic review of how the joint evolution of dense sensing networks, real-time communication systems, big-data analytics, and geospatial platforms is transforming existing atmospheric observation systems into smarter and decision-oriented structures serves as a systematic source for the development of more accurat...
