I recently delivered a virtual keynote address to the Chinese Professionals in Geographic Information Sciences (CPGIS) annual meeting – the main GIS conference in China. Originally scheduled to take place in Nanchang, Jiangxi Province, China, it was switched to an online only conference due to the COVID pandemic; the keynote was pre-recorded.
New paper: Liu, L. and Miller, H.J. (2020) “Does real-time transit information reduce waiting time? An empirical analysis,” Transportation Research A, 141, 167-179.
New publication: Jaegal Y, Miller HJ. (2019) Measuring the structural similarity of network time prisms using temporal signatures with graph indices. Transactions in GIS. 00:1–24. https ://doi.org/10.1111/tgis.12582
Abstract. The network‐time prism (NTP) is an extension of the space‐time prism that provides a realistic model of the potential pattern of moving objects in transportation networks. Measuring the similarity among NTPs can be useful for clustering, aggregating, and querying potential mobility patterns. Despite its practical importance, however, there has been little attention given to similarity measures for NTPs. In this research, we develop and evaluate a methodology for measuring the structural similarity between NTPs using the temporal signature approach. The approach extracts the one‐dimensional temporal signature of a selected property of NTPs and applies existing path similarity measures to the signatures. Graph‐theoretic indices play an essential role in summarizing the structural properties of NTPs at each moment. Two extensive simulation experiments demonstrate the feasibility of the approach and compare the performance of graph indices for measuring NTP similarity. An empirical application using bike‐share system data shows that the method is useful for detecting different usage patterns of two heterogenous user groups.