The UK committed to reduce their greenhouse gas emissions in the year 2050 by 80% or less of the 1990 levels. Passenger vehicles alone accounted for 14% of the total GHG emissions in the UK in the year 2015 (GOV.UK 2015). The aim of this thesis is to investigate the best future scenario and optimal mix of fuels and vehicles to help achieve this commitment. Two linear programming optimisation models were built to map the future mobility pattern of the passenger transport system and investigate the effect of the different parameters and travel behaviours on the cost and emissions of this sector through scenario-based modelling.
The first model describes the behaviour of the passenger transport system with a minimisation objective function of the total cost of fuels and vehicles. Multiple scenarios are investigated by changing the model parameters or constraints to explore their potential in reducing emissions. This model allocates vehicles to trips based on the efficiency of the vehicle when running a certain trip type (driving cycle). It was concluded that trips sharing resulted in the highest CO2 emissions reductions and highest CO2 abatement savings at 1.83 GBP/kg CO2 reduced at year 2050 in reference to the model’s base scenario.
The second model, modifies the previous one by allocating the trips to different rural-urban area profiles. This model investigates the effect of transitioning from the current consumer model where each vehicle is owned and used for all trips types to a full shared ownership system where vehicles are shared between drivers and used with the most efficient trip type. It was concluded that reducing CO2 emission from the shared ownership system resulted in cost savings of 0.9 GBP/kg CO2 reduced in reference to the current ownership model. As a result, both vehicles and trips sharing are recommended for future CO2 reductions at low costs.