Assessing the Impact of Multi-variate Steering-rate Vehicle Control on Driver Performance in a Simulation Framework

When a driver turns a steering-wheel, he or she normally expects the vehicle\u27s steering system to communicate an equivalent amount of signal to the road-wheels. This relationship is linear and occurs regardless of the steering-wheel\u27s position within its rotational travel. The linear steering paradigm in passenger vehicles has gone largely unchanged since mass production of passenger vehicles began in 1901. However, as more electronically-controlled steering systems appear in conjunction with development of autonomous steering functions in vehicles, an opportunity to advance the existing steering paradigms arises. The following framework takes a human-factors approach toward examining and evaluating alternative steering systems by using Modeling and Simulation methods to track and score human performance. Present conventional steering systems apply a linear relationship between the steering-wheel and the road wheels of a vehicle. The rotational travel of the steering-wheel is 900° and requires two-and-a-half revolutions to travel from end-stop to opposite end-stop. The experimental steering system modeled and employed in this study applies a dynamic curve response to the steering input within a shorter, 225° rotational travel. Accommodation variances, based on vehicle speed and steering-wheel rotational position and acceleration, moderate the apparent steering input to augment a more-practical, effective steering rate. This novel model follows a paradigm supporting the full range of steering-wheel actuation without necessitating hand repositioning or the removal of the driver\u27s hands from the steering-wheel during steering maneuvers. In order to study human performance disparities between novel and conventional steering models, a custom simulator was constructed and programmed to render representative models in a test scenario. Twenty-seven males and twenty-seven females, ranging from the ages of eighteen to sixty-five were tested and scored using the driving simulator that presented two successive driving test vignettes: One vignette using conventional 900° steering with linear response and the other employing the augmented 225° multivariate, non-linear steering. The results from simulator testing suggest that both males and females perform better with the novel system, supporting the hypothesis that drivers of either gender perform better with a system augmented with 225° multivariate, non-linear steering than with a conventional steering system. Further analysis of the simulated-driving scores indicates performance parity between male and female participants, supporting the hypothesis positing no significant difference in driver performance between male and female drivers using the augmented steering system. Finally, composite data from written questionnaires support the hypothesis that drivers will prefer driving the augmented system over conventional steering. These collective findings support justification for testing and refining novel steering systems using Modeling and Simulation methods. As a product of this particular study, a tested and open-sourced simulation framework now exists such that researchers and automotive designers can develop, as well as evaluate their own steering-oriented products within a valid human-factors construct. The open-source nature of this framework implies a commonality by which otherwisedisparate research and development work can be associated. Extending this framework beyond basic investigation to reach applications requiring morespecialized parameters may even impact drivers having special needs. For example, steeringsystem functional characteristics could be comparatively optimized to accommodate individuals afflicted with upper-body deficits or limited use of either or both arms. Moreover, the combined human-factors and open-source approaches distinguish the products of this research as a common and extensible platform by which purposeful automotive-industry improvements can be realized—contrasted with arbitrary improvements that might be brought about predominantly to showcase technological advancements

Ubiquitous Integration and Temporal Synchronisation (UbilTS) framework : a solution for building complex multimodal data capture and interactive systems

Contemporary Data Capture and Interactive Systems (DCIS) systems are tied in with various technical complexities such as multimodal data types, diverse hardware and software components, time synchronisation issues and distributed deployment configurations. Building these systems is inherently difficult and requires addressing of these complexities before the intended and purposeful functionalities can be attained. The technical issues are often common and similar among diverse applications. This thesis presents the Ubiquitous Integration and Temporal Synchronisation (UbiITS) framework, a generic solution to address the technical complexities in building DCISs. The proposed solution is an abstract software framework that can be extended and customised to any application requirements. UbiITS includes all fundamental software components, techniques, system level layer abstractions and reference architecture as a collection to enable the systematic construction of complex DCISs. This work details four case studies to showcase the versatility and extensibility of UbiITS framework’s functionalities and demonstrate how it was employed to successfully solve a range of technical requirements. In each case UbiITS operated as the core element of each application. Additionally, these case studies are novel systems by themselves in each of their domains. Longstanding technical issues such as flexibly integrating and interoperating multimodal tools, precise time synchronisation, etc., were resolved in each application by employing UbiITS. The framework enabled establishing a functional system infrastructure in these cases, essentially opening up new lines of research in each discipline where these research approaches would not have been possible without the infrastructure provided by the framework. The thesis further presents a sample implementation of the framework on a device firmware exhibiting its capability to be directly implemented on a hardware platform. Summary metrics are also produced to establish the complexity, reusability, extendibility, implementation and maintainability characteristics of the framework.Engineering and Physical Sciences Research Council (EPSRC) grants - EP/F02553X/1, 114433 and 11394

Temporal multimodal data synchronisation for the analysis of a game driving task using EEG

Multimodal data channels such as bio-physiological signals are increasingly used in game-play studies to better understand players’ behaviours and their motivations. It is however difficult to perform any sort of conclusive analysis solely based on bio-physiological signals due to the complex nature of epistemic, semiotic and ergotic activities surrounding in-game activities and the artefacts facilitating player immersion. Thus a combined analysis of multiple data streams including in-game data and bio-physiological signals is indispensable to produce contextualised information from which a deep analysis of game mechanics and their effects can be performed. Precise synchronisation in capturing multiple streams is required to generate valid inter-stream correlations and meaningful information. Typically there are no automatic mechanisms built in the game architecture or in commercial data logging systems for multimodal data synchronisation and data fusion. This paper presents a novel and generic technique based on inducing identifiable signature pulses in data channels to accurately synchronise multiple temporal data streams. This technique is applied and its capabilities are exhibited using a driving game simulation as an exemplar. In this example, driver’s in-game behavioural data is synchronised and correlated with their temporal brain activity. The concept of simplex method borrowed from linear programming is used to correlate between the driving patterns and brain activity in this initial study is provided so as to allow studying/investigating user behaviour in relation to learning of the driving track