The planning and provision of bus services in Great Britain is currently in a period of transition, with many areas moving towards a franchising system where companies bid to operate parts of a centrally planned network. This growth in coordinated planning of bus networks at city and regional level will mean there is an increased need for modelling tools which can provide accurate forecasts of the number of passengers who might be expected to use different bus stops and services. However, bus demand modelling is a relatively underdeveloped field of analysis, and forecasting tends to be reliant on either ad hoc local analysis or on four-stage transport demand models which are not specifically designed to forecast public transport use. This contrasts with the situation in the railway industry, where there is an extensive body of work on demand forecasting for railway stations and services. This PhD project will therefore aim to develop a set of transferable and user-friendly demand models for bus stops and services, with a particular focus on investigating the transferability of railway demand modelling methods to the bus industry context.
The project will make use of detailed datasets on the usage of existing bus stops and services provided by bus operators and regional transport organisations, along with bus fare and timetable data and a range of datasets on the socio-demographic, economic and land use characteristics of the case study areas. Geographical Information Systems (GIS) will be used to integrate and analyse these datasets, and a range of econometric and statistical modelling methods will be used to develop forecasting models. The use of machine learning methods for demand modelling could also be considered. The models that are developed will be implemented in a modelling tool which could be used by transport authorities and bus operators to assess potential changes to bus service provision.
Applicants must be able to demonstrate that they are comfortable undertaking quantitative analysis and working with large datasets. Previous experience using GIS and some knowledge of British public transport systems would be an advantage.
The project will be supervised by Professor Simon Blainey (s.p.blainey@bham.ac.uk).
Funding notes: Eligibility requirements: requires at least a good 2:1 at undergraduate level in a related discipline (e.g. geography, economics, civil engineering). Funding only available to UK students.
