Analysing the effect of bus service quality improvements on transport energy demand using micro-scale models

Socioeconomic and behavioural factors are vital drivers of energy demand and yet are seldom accounted for in transport-energy models. Transport energy models tend to be technocentric and static in their approach to behaviour, despite evidence suggesting that dramatic changes on the demand side are needed to meet emission reduction targets. Beyond new methods, the scale of the challenge indicates that new frameworks are needed. This research proposes to develop a reproducible and scalable methodology for (a) estimating the quantity and spatial distribution of emissions and energy demand from urban transport and (b) modelling the impact of targeted local interventions on mode shift, emissions and energy demand in UK counties. The results will provide a solid evidence base to support Passenger Transport Executives or Combined Authorities in the UK to decarbonise transport systems nationwide.

More specifically, the research will attempt to answer the following question:

To what extent can improvements in bus service quality lead to a reduction in transport energy demand through a mode shift away from private car travel?

In doing so, the following sub-questions will be explored:

1. What categorisation of individuals and neighbourhoods can be created based on combinations of factors such as socioeconomic characteristics, mode choice, travel patterns, and structural constraints to travel?

2. How can activity-based models be used to estimate energy demand and emissions from passenger transport at an individual level?

3. How can local bus networks be improved to encourage a mode shift away from cars? How can mode shift associated with said improvements be modelled realistically by accounting for behavioural factors? How can scenario modelling be used to compare mode shift and associated energy demand reduction resulting from different service quality improvements in the local bus network?