Innovative passenger vehicle technologies are required to make significant contributions to climate change mitigation. A number of challenges exist as barriers to their adoption. One key opportunity is the potential for social influence to have a positive impact on adoption rates. Social influence is how an individual's decisions can be influenced by other people – what their peers and others say and do and how this, in turn, affects the diffusion of new behaviours. The mixed method research detailed in this thesis contributes to an emerging interest in social influence in transport studies addressing a key research gap, the spatial aspects of this influence. Spatial analysis of private Toyota Prius vehicle ownership, was undertaken at the Output Area level for London for the period 2000 to 2011. Exploratory Spatial Data Analysis (ESDA), an important first step in spatial analysis, indicated the presence of spatial autocorrelation and Toyota Prius spatial clusters ('hotspots'). These 'hotspots' enlarged over time which can be indicative of social influence. This informed the need for in-depth quantitative analysis on the role of co-variables through the use of a Zero Inflated Negative Binomial model and the choice of case study areas for qualitative interviews. In the model, 'what your neighbours do' is a key co-variable represented by the average number of Priuses from neighbouring Output Areas (OA). This measure of social influence had a positive impact on the number of Toyota Priuses in a neighbourhood. The likelihood of Prius ownership in an OA increases by over 50% when the average number of Priuses in neighbouring OA increases by one. The case study OAs were examined in detail setting the scene for the qualitative interviews. Nine face-to-face semi-structured interviews were undertaken with current and potential future Toyota Prius owners. All referenced at least one form of social influence. The influences included direct observation of the vehicles, the opportunity to trial vehicles and changes in the symbolism of the vehicle through its adoption by others. Broader findings were consistent with the literature, for example with regard to the role of congestion charge exemptions and the socio-economic background of the participants. The confirmation of social influence indicated by these findings could assist in the geographic positioning of demonstration schemes or in the allocation of grants, with the economic assessment benefits of grant programmes, because of the 'knock-on' effects of social influence, potentially being wider than conventionally assumed.

This thesis develops dynamic models for the two-mode FWD EVT, develops a control system based on those models that is capable of meeting driver torque demands and performing synchronous mode shifts between different EVT modes while also accommodating preferred engine operating points. The two-input two-output transmission controller proposed herein incorporates motor-generator dynamics, is based on a general state-space integral control structure, and has feedback gains determined using linear quadratic regulator (LQR) optimization. Dynamic modeling of the vehicle is categorized as dynamic modeling of the mechanical and electrical subsystems where the mechanical subsystem consists of the planetary gear sets, the transmission and the engine whereas the electrical subsystem consists of the motor-generator units and the battery pack. A discussion of load torque is also considered as part of the mechanical subsystem. With the help of these derived dynamic models, a distinction is made between dynamic output torque and steady-state output torque. The overall control system consisting of multiple subsystems such as the human driver, power management unit (PMU), friction brakes, combustion engine, transmission control unit (TCU) and motor-generator units is designed. The logic for synchronous mode shifts between different EVT modes is also detailed as part of the control system design. Finally, the thesis presents results for responses in individual operating modes, EVT mode shifting and a full UDDS drive cycle simulation.