Postgrad LIVE! Study Fairs

Birmingham | Edinburgh | Liverpool | Sheffield | Southampton | Bristol

University of Birmingham Featured PhD Programmes
University of Kent Featured PhD Programmes
Swansea University Featured PhD Programmes
Imperial College London Featured PhD Programmes
University of Manchester Featured PhD Programmes

Modelling Travel Behaviour of Elderly People using Smart Card Data

This project is no longer listed in the FindAPhD
database and may not be available.

Click here to search the FindAPhD database
for PhD studentship opportunities
  • Full or part time
    Dr C Choudhury
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

About This PhD Project

Project Description


The ease of mobility is an important aspect of the quality of life of the elderly people. Yet, there have been very few researches that have focused on analyzing the travel behaviour of the elderly population or attempted to develop detailed mathematical models to predict how their travel patterns may change in response to changes in the transport planning and operational policies. This is primarily attributed to the lack of detailed data.

The availability of the England National Concessionary Travel Scheme data (i.e. smartcard data for the over 65s, blind and disabled) from the West Yorkshire Combined Authority (WYCA) offers the promise to extract timestamped footprints of thousands of elderly public transport users over a long timespan. However, the data has certain limitations. For instance, the available information includes the boarding time of the user, the bus line that has been used and the sub-zone from where he/she has boarded. The origin bus stop can be inferred by combining this data with the travel time records that are collected for performance measurements. Still, the destinations and the true trip origins (beyond the bus stop) are unobserved. Moreover, only a limited number of socio-demographic characteristics of the users are available from WYCA. This warrants the need to investigate methodologies that can address these data issues before using them for developing mathematical models of travel behaviour. Existing data sources like National Travel Survey, British Household Panel, and etc. or small scale supplementary surveys may be fused with the smart card data to account for these data limitations.

Aims and Approach

The proposed project will address the above mentioned research gap by formulating detailed methodologies to account for the limitations of the ENCTS smart card data and developing mathematical modelling frameworks to combine these with more traditional data sources in the context of modelling travel behaviour of the elderly people in West Yorkshire. The proposed approaches are likely to include a combination of statistical data mining and econometric approaches.

Impact of Research

The developed models will be useful for WYCA in demand management and predicting the impact of alternate policies on the mobility of the elderly population. Thus, it can indirectly contribute to improvement of the quality of life of the senior citizens. Moreover, the methodologies used in combining different data sources will be also useful for analyzing travel behaviour of general users once the relevant smart card data which are currently unavailable, but likely to be available in near future.

Training, Partners and Collaborators

West Yorkshire Combined Authority

Entry Requirements/Necessary Background:
The minimum requirement is a UK Upper Second Class Honours or equivalent in a Quantitative Discipline. Desired skills include strong numerical aptitude, some experience in computer programming, interest in transport modelling and Big Data.

Please visit our LARS scholarship page for more information and further opportunities:


Pelletier, M. P., Trépanier, M., & Morency, C. (2011). Smart card data use in public transit: A literature review. Transportation Research Part C: Emerging Technologies, 19(4), 557-568.

Chakirov, A., & Erath, A. (2012). Activity identification and primary location modelling based on smart card payment data for public transport.

FindAPhD. Copyright 2005-2018
All rights reserved.