Evaluating and Predicting the Impact of Roadworks Using Mobile Phone Data
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Roadworks affect road users all over the globe impacting society as a whole through loss of valuable time (Ministerie van Infrastructuur en Milieu, 2015; Schrank, Eisele, & Lomax, 2012). To improve our understanding of the impact roadworks on society as a whole, we need to move to a new source of information. Current techniques, such as surveys and road side measurements, require a lot of effort and resources to investigate the impact of a single roadwork (Taale, Schuurman, & Bootsma, 2002; Cáceres, Wideberg, Benitez, 2007). The costs of traditional technique imply research on the true economic impact of roadworks is only scarcely performed. Hence, we are in need of an alternative source of information if we want to learn more about the impact of roadworks. In this research we propose mobile phone data, i.e. mobility data extracted from Call Detail Records (CDRs), as a viable alternative. We will present a method to measure the impact of roadworks using mobile phone data. Furthermore, we validate the presented method by comparing the outcomes with traditional information sources such as surveys, road side measurements, and GPS traces. The standard mobile phone data will be fine-tuned to elicit more accurate origins and destinations. After fine-tuning, we find the mobile phone data delivers results similar to the traditional sources with much greater ease and at unprecedented scale. Moreover, we show we can enrich the mobile phone data with data about crucial trip motives, e.g. home-to-work, previously only present in mobility surveys. These motives can then be used to measure the economic impact to society rather than travel time loss (Kennisinstituut voor Mobiliteitsbeleid, 2013). Where traditional techniques would require months of research to measure the impact of one roadwork; we show that mobile phone data can measure hundreds with a fraction of the time and effort. The rich and plentiful information present in the mobile phone data will also be used to predict the impact of roadworks. Using this new found source of information, we investigate the underlying structures that result in delays and uncertainties in travel times due to roadworks. We, for one, create models that explain up to 45% of the variation in the measured impact and suggest research directions to further increase this percentage.