Data Fusion for MaaS: Opportunities and Challenges

Publication Type:
Conference Proceeding
Citation:
Proceedings of the 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design, CSCWD 2018, 2018, pp. 184 - 189
Issue Date:
2018-09-13
Filename Description Size
cscwdV16.pdfAccepted Manuscript594.59 kB
Adobe PDF
Full metadata record
© 2018 IEEE. Computer Supported Cooperative Work (CSCW) in design is an essential facilitator for the development and implementation of smart cities, where modern cooperative transportation and integrated mobility are highly demanded. Owing to greater availability of different data sources, data fusion problem in intelligent transportation systems (ITS) has been very challenging, where machine learning modelling and approaches are promising to offer an important yet comprehensive solution. In this paper, we provide an overview of the recent advances in data fusion for Mobility as a Service (MaaS), including the basics of data fusion theory and the related machine learning methods. We also highlight the opportunities and challenges on MaaS, and discuss potential future directions of research on the integrated mobility modelling.
Please use this identifier to cite or link to this item: