A Real-Time Game Theoretic Planner for Autonomous Two-Player Drone Racing

To be successful in multi-player drone racing, a player must not only follow the race track in an optimal way, but also compete with other drones through strategic blocking, faking, and opportunistic passing while avoiding collisions. Since unveiling one's own strategy to the adversaries is not desirable, this requires each player to independently predict the other players' future actions. Nash equilibria are a powerful tool to model this and similar multi-agent coordination problems in which the absence of communication impedes full coordination between the agents. In this paper, we propose a novel receding horizon planning algorithm that, exploiting sensitivity analysis within an iterated best response computational scheme, can approximate Nash equilibria in real time. We also describe a vision-based pipeline that allows each player to estimate its opponent's relative position. We demonstrate that our solution effectively competes against alternative strategies in a large number of drone racing simulations. Hardware experiments with onboard vision sensing prove the practicality of our strategy

Being Jacques Villeneuve: Formula One, 'Agency' and the Fan

DVD disc of supplementary material available with the print copy of this thesis, held at the University of Waikato Library.In this thesis, I analyse my fandom for the Formula One driver, Jacques Villeneuve. Despite its rampant commercialism, innovative mediation, prestige and popular status within global sport, Formula One is surprisingly an under-researched topic in academia. Moreover, 'intense' fandom has often been stigmatised; at worst associating such individuals with pathological and obsessive behaviours or refuting their affections as merely symptomatic of the socio-economic forces that transform fans into duped consumers. This thesis argues against such simplistic disqualifications and reconceptualises fandom in light of how the structure/agency binary has itself been reconceptualised within media and cultural studies. Rather than privileging either the determining social, mediated and commercial structures, or championing the 'active agential' capacities of social individuals, Grossberg's notions of 'affect' and 'structured mobility' are drawn upon to underpin a more flexible explanation of contemporary fandom. In particular, affect offers theoretical purchase for how fans form attachments with selective media objects and why these come to 'matter' for specific individuals. Furthermore, by marrying affect with 'structured mobility', affective investments are recognised for their capacity to 'anchor' individuals in specific and concrete spatial/temporal 'moments' of social reality as they navigate both the mediated apparatus of the sport and the structured social, cultural and economic terrain that shapes their mediated fandom. Such insights are developed through a 'funnelling' approach in this thesis which moves from an examination of collective Formula One fandom to my own, exploring the affective traces of a friction that Villeneuve's maverick status provided within the broader machinery of the sport and to which this fan has responded

The design-by-adaptation approach to universal access: learning from videogame technology

This paper proposes an alternative approach to the design of universally accessible interfaces to that provided by formal design frameworks applied ab initio to the development of new software. This approach, design-byadaptation, involves the transfer of interface technology and/or design principles from one application domain to another, in situations where the recipient domain is similar to the host domain in terms of modelled systems, tasks and users. Using the example of interaction in 3D virtual environments, the paper explores how principles underlying the design of videogame interfaces may be applied to a broad family of visualization and analysis software which handles geographical data (virtual geographic environments, or VGEs). One of the motivations behind the current study is that VGE technology lags some way behind videogame technology in the modelling of 3D environments, and has a less-developed track record in providing the variety of interaction methods needed to undertake varied tasks in 3D virtual worlds by users with varied levels of experience. The current analysis extracted a set of interaction principles from videogames which were used to devise a set of 3D task interfaces that have been implemented in a prototype VGE for formal evaluation

A Real-Time Game Theoretic Planner for Autonomous Two-Player Drone Racing

In this article, we propose an online 3-D planning algorithm for a drone to race competitively against a single adversary drone. The algorithm computes an approximation of the Nash equilibrium in the joint space of trajectories of the two drones at each time step, and proceeds in a receding horizon fashion. The algorithm uses a novel sensitivity term, within an iterative best response computational scheme, to approximate the amount by which the adversary will yield to the ego drone to avoid a collision. This leads to racing trajectories that are more competitive than without the sensitivity term. We prove that the fixed point of this sensitivity enhanced iterative best response satisfies the first-order optimality conditions of a Nash equilibrium. We present results of a simulation study of races with 2-D and 3-D race courses, showing that our game theoretic planner significantly outperforms amodel predictive control (MPC) racing algorithm. We also present results of multiple drone racing experiments on a 3-D track in which drones sense each others'' relative position with onboard vision. The proposed game theoretic planner again outperforms the MPC opponent in these experiments where drones reach speeds up to 1.25m/s

Prize Structure and Performance: Evidence from NASCAR

The predictions that emerge from tournament theory have been tested in a number of sports-related settings. Since sporting events involving individuals (golf, tennis, running, auto racing) feature rank order tournaments with relatively large payoffs and easily observable outcomes, sports is a natural setting for such tests. In this paper, we test the predictions of tournament theory using a unique race-level data set from NASCAR. Most of the previous tests of tournament theory using NASCAR data have used either season level data or race level data from a few seasons. Our empirical work uses race level NASCAR data for 1,114 races over the period 1975-2009. Our results support the predictions of tournament theory: the larger the spread in prizes paid in the race, measured by the standard deviation of prizes paid or the interquartile range of prizes paid, the higher the average speed in the race. Our results account for the length of the track, the number of entrants, the number of caution flags, and unobservable year and week heterogeneity.NASCAR; tournament theory