This thesis explores whether ‘business model innovation’ could hold the key to advancing the ultra-low and zero carbon vehicle industry in the United Kingdom. This thesis presents a critical comparison of two case studies drawn from qualitative research conducted with a broad cross-section of UK vehicle manufacturers (VMs) that are interested in introducing zero carbon vehicles to the marketplace. The two cases, looking at large established producers of vehicles with trans-national presence (herein termed TNC/MNC VMs) and smaller producers (herein termed SME VMs). The two cases consist of a number of grouped embedded cases focusing on the activities of vehicle producers that are in the process of introducing Ultra-Low Emission Vehicles (ULEVs) to the UK marketplace. These cases are constructed and informed by both primary research, semi-structured interviews conducted with representatives of these VMs, secondary analysis of interviews conducted with VM representatives and industry commentators and documentary analysis of contemporary sources and industry commentary. The thesis is framed within a broader academic debate regarding the nature of achieving socio-technical transitions. Within this frame of reference, particular attention is paid to the role of large incumbents vs. new start-up insurgents in bringing innovative technologies to the marketplace; innovative technologies being seen as a key component of a transition to a more sustainable world. In comparing the business models of large, well-established vehicle manufacturers, with smaller, newer, SME providers the ontology of Business Models developed by Osterwalder & Pigneur (2002) is used to interrogate, analyse and make comparisons between the business models of a range of companies that are very dissimilar in nature. Context is crucial to understanding the detail of case studies; as such, the thesis is also informed by the perspectives, gained through interviews, of a number of industry commentators, representatives of government organisations and automotive trade bodies. ~ xxviii ~ This thesis set out to explore a number of research themes and the contributions to knowledge that this thesis has made are: Establishing a theoretical linkage between Geels (2006) multi-level perspective of transitions literature and Osterwalder & Pigneur’s (2002) business model ontology. By bringing these two powerful tools together, it is proposed that a complimentary analysis of the business model on the micro level, embedded within an overall socio-technical transition at the macro level can be made. Furthermore, through an empirical analysis of business models in the car industry, a range of business model components, new directions for business models and “complementary” ancillary business models that support the introduction of ULEVs has been identified. Disappointingly, whilst some observation are made about the early stages of transitions, the slow uptake of ULEVs in the marketplace has shown that the incumbent regime is still reistant to transition – and no concrete transition mechanisms can be identified. There are however a collection of observations about the early stages of socio-technical transitions. The thesis also contributes to the ongoing debate about the tensions between incumbent and insurgent business contributing to the ongoing characterisation of the competitive forces that exist between them. Another important contribution to the business models literature, is a discussion of the role of product, process and business model design. Very recent work by Meertens, Starreveld, Iacob, & Nieuwenhuis (2013) has also explored this issue, however, this work takes a different perspective informed by the empirical data within the case studies.

It is often acknowledged that movement exists in multiple, interdependent forms and that we live in an Information Age. However, mobilities perspectives on contemporary cycling tend to neglect the a) interconnections between transport (physical mobility of people and objects) and communication (mobility of symbolic information) b) paradigmatic shifts in modernity that affect how and why we communicate about transport. This thesis responds to such neglect. Firstly, it places urban cycling in an internet context by examining practices and perceptions of policy blogging, asking why do individuals blog about cycling-related transport policy and to what effect? Secondly, it analyses the answers to these questions through the theoretical lens of the risk society and reflexive modernisation theses. Empirical data is the result of 46 semi-structured interviews with bloggers and expert system representatives, mostly in London, New York and Paris. Blogging about cycling-related transport policy is shown to be an individualised response to the perceived failings of expert systems, as well as in Giddens’ words, a ‘reflexive project of the self’. Citizens who may otherwise only be policy subjects or passive consumers of transport, emerge as policy, media and civil society actors by virtue of their ability to publish information, which forms the basis of social relations. Through blogging, they produce and mobilise knowledge. Knowledge claims mediated by blogging interact with expert systems responsible for transport, which in turn adapt; routine institutional practices evolve; a new order emerges; blogging makes a difference. That difference is however limited, not least because the public remains reliant on expert systems. Ultimately, despite the obvious importance of physical mobility to cycling, this thesis seeks to move beyond it. Information and communication technologies have radically altered how we - researchers, the public, expert system representatives - communicate about and understand cycling, and as such, this project argues for a renewed emphasis on mobilities in a genuinely plural sense of the word as being about more than physically moving from A to B.

<p> This project presents the design, implementation and experimental demonstration of an intensity control system for highway lighting. High Intensity Discharge lights (HID) are replaced by the White Light Emitting diodes (LED) in highway lighting systems in order to incorporate the dimming feature and conserve energy. The intensity is controlled by utilizing a micro controller that belongs to the 8051 family by generating pulse width modulated signals that energize a metal-oxide-semiconductor field effect transistor (MOSFET) to switch the LEDs to accomplish the desired operation. </p><p> A working model using ATMEL has been developed in which an array of LEDs are connected in series and parallel to control the light intensity applicable to the highway lights, which makes it a real time system. The micro controller is programmed to keep light intensity high during peak traffic hours, and gradually reduce it as traffic decreases, until dawn when lights are turned off to save energy.</p>

<p> The increasing trend in crashes and consequent fatalities due to distracted driving is a growing safety concern in our road network. With rapid advancement in cellphone and in-vehicle technologies along with driver&rsquo;s inclination to multitasking, the number of crashes due to distracted driving are further on the rise. Some previous studies attempted to detect distracted driving behavior in real-time to mitigate this issue. However, these studies mainly focused on detecting either visual or cognitive distractions, while most of the real-life distracting tasks involve driver&rsquo;s visual, cognitive, and physical workload, simultaneously. Additionally, previous studies frequently used eye, head, or face tracking data, although current vehicles are not equipped with technologies to acquire such data. To address above issues, this driving simulator study focused on developing algorithms for detecting specific distraction tasks using only vehicle control and driving performance measures. Specifically, algorithms were developed to detect two distracting tasks &ndash; texting and eating/drinking. Three data mining techniques were explored &ndash; Linear Discriminant Analysis (LDA), Logistic Regression (LR), and Support Vector Machine (SVM). SVM algorithms found to outperform LDA and LR, which detected texting and eating/drinking distraction with an accuracy of 84.33% and 79.53%, respectively. This study may provide useful guidance to successful implementation of distracted driver detection algorithm in Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communication, as well as to auto manufacturers interested in integrating distraction detection systems in their vehicles. </p>

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published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

published_or_final_version / abstract / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning