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Modelling car-sharing choice using extreme value theory


About This PhD Project

Project Description

Increasing traffic congestion and the resultant greenhouse gas emissions and local air pollution are a major public policy concern, and have stimulated a substantial body of research aimed at developing sustainable forms of people mobility and freight distribution. Travellers’ behaviour is currently undergoing a shift from owning vehicles to using and sharing services. This provides an opportunity to acquaint users with electrified L-category vehicles (EL-Vs) which are smaller, lighter and more specialised than other vehicles, and could produce economic savings in terms of time gained, energy consumption and space required for moving and parking. These issues are being addressed in the ELVITEN project which is funded by the Horizon 2020 programme. ELVITEN will carry out one-year long demonstrations with hundreds of EL-Vs of all categories in six European cities (Genoa, Rome, Bari, Malaga, Berlin and Trikala) and collect a big data bank of trip data and users’ experiences and opinions after the trips. Such data can be used to accurately predict users’ preferences on different vehicle types and their vehicle usage.

The proposed PhD project will focus on the development and application of extreme value theory (EVT) to model users’ choice behaviour which involves choosing multiple vehicle types simultaneously and allocating continuous amounts of budget to the chosen vehicles. EVT model estimates the impacts of a set of socio-demographic attributes (e.g. user age, income level, driving license country, insurance plan, membership plan, and origin location) on user’s vehicle choice and capture the satiation effect with increasing the consumption for each vehicle type. The project will also address how the theoretical outputs can be used by operators when determining the most efficient allocation of resources within sharing services.

This project will be supervised jointly by the Department of Statistics and the Institute for Transport Studies at Leeds, and will also involve strong research collaboration with an industrial partner called S3Transportation (Smart, Safe and Sustainable Transportation).

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