Tyron Louw

Bio: Tyron Louw is an academic researcher from University of Leeds. The author has contributed to research in topics: Driving simulator & Poison control. The author has an hindex of 14, co-authored 43 publications receiving 1019 citations. Previous affiliations of Tyron Louw include Rhodes University.

What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems

Abstract: The main aim of this study was to use an adapted version of the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate the factors that influence users’ acceptance of automated road transport systems (ARTS). A questionnaire survey was administered to 315 users of a CityMobil2 ARTS demonstration in the city of Trikala, Greece. Results provide evidence of the usefulness of the UTAUT framework for increasing our understanding of how public acceptance of these automated vehicles might be maximised. Hedonic Motivation, or users’ enjoyment of the system, had a strong impact on Behavioural Intentions to use ARTS in the future, with Performance Expectancy, Social Influence and Facilitating Conditions also having significant effects. The anticipated effect of Effort Expectancy did not emerge from this study, suggesting that the level of effort required is unlikely to be a critical factor in consumers’ decisions about using ARTS. Based on these results, a number of modifications to UTAUT are suggested for future applications in the context of automated transport. It is recommended that designers and developers should consider the above issues when implementing more permanent versions of automated public transport.

Acceptance of Automated Road Transport Systems (ARTS): An adaptation of the UTAUT model

Abstract: As research into innovative forms of automated transportation systems gains momentum, it is important that we develop an understanding of the factors that will impact the adoption of these systems. In an effort to address this issue, the European project CityMobil2 is collecting data around large-scale demonstrations of Automated Road Transport Systems (ARTS) in a number of cities across Europe. For these systems to be successful, user acceptance is vital. The current study used the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate the factors which might influence acceptance of ARTS vehicles, which were operational in two locations in Europe. The results indicate that the UTAUT constructs of performance expectancy, effort expectancy and social influence were all useful predictors of behavioural intentions to use ARTS, with performance expectancy having the strongest impact. However, it would appear that other factors are also needed in order for the model to strongly predict behavioural intentions in an automated transport context. Based on these findings, a number of implications for developers and ideas for future research are suggested.

Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations

Abstract: Automated vehicles (AV) are expected to be integrated into mixed traffic environments in the near future. As human road users have established elaborated interaction strategies to coordinate their actions among each other, one challenge that human factors experts and vehicle designers are facing today is how to design AVs in a way that they can safely and intuitively interact with other traffic participants. This paper presents design considerations that are intended to support AV designers in reducing the complexity of the design space. The design considerations are based on a literature review of common human–human interaction strategies. Four categories of information are derived for the design considerations: (1) information about vehicle driving mode; (2) information about AVs’ manoeuvres; (3) information about AVs’ perceptions of the environment; and (4) information about AVs’ cooperation capabilities. In this paper, we apply the four categories to analyse existing research studies of traffic participants’ needs during interactions with AVs and results of the CityMobil2 project. From the CityMobil2 project we present central results from face-to-face interviews, an onsite-survey and two focus groups. To further support the AV designers we describe and rate different design options to present the information of the four categories, including the design of the infrastructure, the vehicle shape, the vehicle manoeuvres and the external human–machine interface of the AV.

Are you in the loop? Using gaze dispersion to understand driver visual attention during vehicle automation

Abstract: This driving simulator study, conducted as part of the EC-funded AdaptIVe project, assessed drivers’ visual attention distribution during automation and on approach to a critical event, and examined whether such attention changes following repeated exposure to an impending collision. Measures of drivers’ horizontal and vertical gaze dispersion during both conventional and automated (SAE Level 2) driving were compared on approach to such critical events. Using a between-participant design, 60 drivers (15 in each group) experienced automation with one of four screen manipulations: (1) no manipulation, (2) manipulation by light fog, (3) manipulation by heavy fog, and (4) manipulation by heavy fog with a secondary task, which were used to induce varying levels of engagement with the driving task. Results showed that, during automation, drivers’ horizontal gaze was generally more dispersed than that observed during manual driving. Drivers clearly looked around more when their view of the driving scene was completely blocked by an opaque screen in the heavy fog condition. By contrast, horizontal gaze dispersion was (unsurprisingly) more concentrated when drivers performed a visual secondary task, which was overlaid on the opaque screen. However, once the manipulations ceased and an uncertainty alert captured drivers’ attention towards an impending incident, a similar gaze pattern was found for all drivers, with no carry-over effects observed after the screen manipulations. Results showed that drivers’ understanding of the automated system increased as time progressed, and that scenarios that encourage driver gaze towards the road centre are more likely to increase situation awareness during high levels of automation.

Using Multivariate Statistics

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贝叶斯滤波与平滑 (Bayesian filtering and smoothing)

Abstract: Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications, and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book’s practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include MATLAB computations, and the numerous end-of-chapter exercises include computational assignments. MATLAB/GNU Octave source code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.

Takeover Time in Highly Automated Vehicles: Noncritical Transitions to and From Manual Control:

Abstract: Objective:The aim of this study was to review existing research into driver control transitions and to determine the time it takes drivers to resume control from a highly automated vehicle in noncr...