Institute for Transport Studies (ITS)

Enhancing transport models combining mobile phone data with traditional data sources

Supervisor: Dr Charisma Choudhury

Transport and mobility models have traditionally relied on survey data which expensive to collect and thereby have limited sample sizes and lower update frequencies. Moreover, they are prone to sampling biases and reporting errors.

Over the last decade, mobile phone penetration rates have increased manifold both in developed and developing countries: the current penetration rates being 128% and 89% in developed and developing countries respectively. Subsequently, mobile phone data has emerged as a very promising source of data for transportation researchers. In recent years, mobile phone data have been used for human travel pattern visualization, mobility pattern extraction, route choice modelling, traffic model calibration, traffic flow estimation, origin-destination estimation to name a few. The transport models using mobile phone data however is yet to reach its full potential, particularly due to the issue regarding treatment of missing information (e.g. data gaps, lack of background information about the user) and accounting for potential biases.

The dissertation will look into combining mobile phone data with data from other sources: household surveys, GPS traces, sensor counts, etc. and develop robust transport models that utilize the strengths of the mobile phone data to complement the other data sources. This will involve exploring econometric and/or simulation based approaches.

Links:

Iqbal MS; Choudhury CF; Wang P; González MC (2014) Development of origin-destination matrices using mobile phone call data, Transportation Research Part C: Emerging Technologies, 40, pp.63-74.

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