Efficient Data Management for Intelligent Urban Mobility Systems

Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with this data presents unique challenges of data management, processing and presentation that is often overlooked by researchers. Therefore, in this work we present an integrated data management and processing framework for intelligent urban mobility systems currently in use by our partner transit agencies. We discuss the available data sources and outline our cloud-centric data management and stream processing architecture built upon open-source publish-subscribe and NoSQL data stores. We then describe our data-integrity monitoring methods. We then present a set of visualization dashboards designed for our transit agency partners. Lastly, we discuss how these tools are currently being used for AI-driven urban mobility applications that use these tools.

[1]  Keiichi Yasumoto,et al.  Time-dependent Decentralized Routing using Federated Learning , 2020, 2020 IEEE 23rd International Symposium on Real-Time Distributed Computing (ISORC).

[2]  Aron Laszka,et al.  Data-Driven Prediction of Route-Level Energy Use for Mixed-Vehicle Transit Fleets , 2020, 2020 IEEE International Conference on Smart Computing (SMARTCOMP).

[3]  Keiichi Yasumoto,et al.  On Decentralized Route Planning Using the Road Side Units as Computing Resources , 2020, 2020 IEEE International Conference on Fog Computing (ICFC).

[4]  Keiichi Yasumoto,et al.  Smart Transportation Delay and Resiliency Testbed Based on Information Flow of Things Middleware , 2019, 2019 IEEE International Conference on Smart Computing (SMARTCOMP).

[5]  Shaohua Wang,et al.  An integrated GIS platform architecture for spatiotemporal big data , 2019, Future Gener. Comput. Syst..

[6]  Rafal A. Angryk,et al.  Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases , 2016 .

[7]  Alexander Garcia Department of Finance and Administration , 2015 .

[8]  M. Sheelagh T. Carpendale,et al.  Visits: A Spatiotemporal Visualization of Location Histories , 2013, EuroVis.

[9]  Patrick Weber,et al.  OpenStreetMap: User-Generated Street Maps , 2008, IEEE Pervasive Computing.

[10]  Sanglu Lu,et al.  Spatiotemporal data modelling and management: a survey , 2000, Proceedings 36th International Conference on Technology of Object-Oriented Languages and Systems. TOOLS-Asia 2000.