Session 2015-2016 – Closing Date: 13 March 2015 (23:59 UK time)

Principal Supervisor

Dr Charisma Choudhury

Tel No: 0113 3432659

E-Mail: c.f.choudhury<στο>leeds.ac.uk

Project Description

Transport and mobility models have traditionally relied on manually collected survey data which are expensive to obtain and thereby generally have limited sample sizes and lower update frequencies and are prone to biases and reporting errors. On the other hand, over the last decade, passively collected big data sources have emerged as a very promising source of mobility data for researchers and practitioners. These include GPS tracts, mobile phone records, card transactions and geo-coded social-media data which have been used successfully for human travel pattern visualization, route choice modelling, traffic model calibration and traffic flow estimation. Despite the obvious opportunity to reduce survey costs and improve information availability in a transportation planning context, methodological limitations and practical issues have reduced the applicability (and acceptability) of these passively collected data in practice.

This research proposes to combine mobile phone and GPS data with data from traditional sources (household surveys, census, roadside interviews and sensor counts) and develop robust transport models that utilize the strengths of the mobile phone and GPS data to complement the traditional data sources and vice versa. In particular, measures to account for the sampling bias, coarse resolution, discontinuities and lack of user info in the data will be investigated and solutions will be formulated. Both empirical and simulation based methodologies will be explored in this regard.

Effective use of emerging data will enable us to develop stronger, more comprehensive models, faster and cheaper – removing previous barriers for smaller authorities or poorer countries.

Entry Requirements  

The minimum requirement is a UK Upper Second Class Honours or equivalent in a Quantitative Discipline.

Desired skills:

• Strong numerical aptitude
• Some experience in computer programming
• Interest in transport modelling and Big Data

Application Process Contact Name Deborah Goddard Tel No +44 113 3435326

E-Mail: d.a.goddard<στο>leeds.ac.uk

How to Apply for an ESRC WR DTC Studentship at Leeds:

Applicants must first submit the relevant study application form(s) and be in receipt of a Student ID Number. Applicants must then complete the University’s ESRC WR DTC Studentship Application Form (click here for application form). This should be returned to pg_scholarships<στο>leeds.ac.uk by the relevant deadline. Details of other ESRC WR DTC Studentships at the University of Leeds can be found at:www.leeds.ac.uk/rsa/postgraduate_scholarships/esrc-info

http://www.leeds.ac.uk/rsa/postgraduate_scholarships/esrc-infoFull awards will cover UK/EU academic fees and a maintenance grant paid at standard Research Council rates (£13,863 tax free in Session 2014/15) for full-time study (part-time study will be pro-rata) together with other allowances if appropriate. EU applicants will be eligible for an award paying tuition fees only, except in exceptional circumstances, or where residency has been established for more than 3 years prior to the start of the course. 

In addition to access to the research and training facilities at the Institute for Transport Studies, the student will have the opportunity to work in close collaboration with Mott MacDonald and get valuable insights on issues associated with the hands on application of the research, which is generally a rare opportunity for a PhD student.