A Novel Approach to Road Matching Based on Cell Phone Handover

Modelling long-distance route choice using mobile phone call detail record data: a case study of Senegal

“…Leontiadis et al (2014) calculate the weights for each road segment within the cell areas linked to a user's communication events and determine the shortest weighted path for a given OD pair. Nie et al (2015) mark each route with a subset of k optimal cell handover sequences extracted from the full set of possible handover sequences and match these with those observed in the cell phone hand over data (similar to CDR data) based on the degree of similarity. In this study, we follow a slightly similar approach, however, instead of using a similarity index, we pursue the idea of unique and shared location area sequences in the context of broad choice modelling as explained later.…”

“…A review of literature shows that there have been a few route identification studies using network-generated mobile phone data (e.g. Nie et al, 2015, Leontiadis et al, 2014, Hoteit et al, 2014, however, most of these studies end on route identification and do not attempt to investigate the factors affecting route choice behaviour. At the moment, only Schlaich (2010) combines GSM trajectories with traffic state information to analyse the influence of variable message signs (VMS) and other factors on route choice.…”