Principles of adjustable autonomy: a framework for resilient human–machine cooperation

Unmanned ground vehicles tend to be more and more autonomous, but both complete teleoperation and full autonomy are not efficient enough to deal with all possible situations. To be efficient, the human–robot system must be able to anticipate, react and recover from errors of different kinds, i.e., to be resilient. From this observation, this paper proposes a survey on the resilience of a human–machine system and the means to control the resilience. The resilience of a system can be defined as the ability to maintain or recover a stable state when subject to disturbance. Adjustable autonomy and human–machine cooperation are considered as means of resilience for the system. This paper then proposes three indicators to assess different meanings of resilience of the system: foresight and avoidance of events, reaction to events and recovery from occurrence of events. The third of these metrics takes into consideration the concept of affordances that allows a common representation for the opportunities of action between the automated system and its environment.     

Spectral registration of noisy sonar data for underwater 3D mapping

3D mapping is very challenging in the underwater domain, especially due to the lack of high resolution, low noise sensors. A new spectral registration method is presented that can determine the spatial 6 DOF transformation between pairs of very noisy 3D scans with only partial overlap. The approach is hence suited to cope with sonar as the predominant underwater sensor. The spectral registration method is based on Phase Only Matched Filtering (POMF) on non-trivially resampled spectra of the 3D data.     

Nano-structured solid oxide fuel cell design with superior power output at high and intermediate operation temperatures

A solid oxide fuel cell (SOFC) with a thin-film yttria-stabilized zirconia (YSZ) electrolyte was developed and tested. This novel SOFC shows a similar multilayer set-up as other current anode-supported SOFCs and is composed of a Ni/8YSZ anode, a gas-tight 8YSZ electrolyte layer, a dense Sr-diffusion barrier layer and a LSCF cathode. To increase the power density and lower the SOFC operating temperature, the thickness of the electrolyte layer was reduced from around 10 μm in current cells to 1 μm, using a nanoparticle deposition method. By using the novel 1 μm electrolyte layer, the current density of our SOFC progressed to 2.7, 2.1 and 1.6 A/cm² at operation temperatures of 800, 700 and 650°C, respectively, and out-performs all similar cells reported to date in the literature. An important consideration is also that cost-effective dip-coating and spin-coating methods are applied for the fabrication of the thin-film electrolyte. Processing of 1 μm layers on the very porous anode substrate material was initially experienced as very difficult and therefore 8YSZ nanoparticle coatings were developed and optimized on porous 8YSZ model substrates and transferred afterwards to regular anode substrates. In this paper, the preparation of the novel SOFC is shown and its morphology is illustrated with high resolution SEM pictures. Further, the performance in a standard SOFC test is demonstrated.     

Mixed-Signal Approximate Computation: A Neural Predictor Case Study

As transistors shrink and processors trend toward low power, maintaining precise digital behavior grows more expensive. Replacing digital units with analog equivalents sometimes allows similar computation to be performed at higher speed using less power. As a case study in mixed-signal approximate computation, the authors describe an enhanced neural prediction algorithm and its efficient analog implementation.     

Traffic analysis and synthetic models of second life

Virtual Worlds (VW), such as Massive Multiplayer Online Social Games, have been gaining increasing attention in the last few years, mainly due to the new way users interact with them. However, little effort has been devoted to understand their traffic profile and the implications to the traffic management area. With the current growing rate of VWs’ usage, their traffic demand could eventually impose a significant burden on the operation of a typical Internet Service Provider (ISP) network. In this paper, we seek to understand the traffic behavior of an increasingly popular VW application, namely Second Life (SL), from both the connection and network level perspectives. We also show results of a traffic analysis of a SL client, when an avatar performs different actions in the VW, at different places and under different network conditions. Our results show that SL makes intensive use of network resources (mostly bandwidth), since the capacity needed for having a full SL experience (listening to live music) may reach 500 kbps. We then extend the traffic analysis work on SL by providing analytical models for its traffic profile. We aim at helping the network management and planning area to estimate the impact of an intense use of such VW on access links or core networks. Such synthetic models are also useful to the networking research community for the use in network simulations.     

A comprehensive quality model for service-oriented systems

In a service-oriented system, a quality (or Quality of Service) model is used (i) by service requesters to specify the expected quality levels of service delivery; (ii) by service providers to advertise quality levels that their services achieve; and (iii) by service composers when selecting among alternative services those that are to participate in a service composition. Expressive quality models are needed to let requesters specify quality expectations, providers advertise service qualities, and composers finely compare alternative services. Having observed many similarities between various quality models proposed in the literature, we review these and integrate them into a single quality model, called QVDP. We highlight the need for integration of priority and dependency information within any quality model for services and propose precise submodels for doing so. Our intention is for the proposed model to serve as a reference point for further developments in quality models for service-oriented systems. To this aim, we extend the part of the UML metamodel specialized for Quality of Service with QVDP concepts unavailable in UML.

Naturalistic study of the risky situations faced by novice riders

This article sets out to identify the typical risky situations experienced by novice motorcyclists in the real world just after licensing. The procedure consists of a follow-up of six novices during their first two months of riding with their own motorbike instrumented with cameras. The novices completed logbooks on a daily basis in order to identify the risky situations they encountered, and were given face-to-face interviews to identify the context and their shortcomings during the reported events. Data show a large number of road configurations considered as risky by the riders (248 occurrences), especially during the first two weeks. The results revealed that a lack of hazard perception skills contributed to the majority of these incidents. These situations were grouped together to form clusters of typical incident scenarios on the basis of their similarities. The most frequent scenario corresponds to a lane change in dense traffic (15% of all incidents). The discussion shows how this has enhanced our understanding of novice riders’ behaviour and how the findings can improve training and licensing. Lastly, the main methodological limitations of the study and some guidelines for improving future naturalistic riding studies are presented.

Practitioner Summary:

This article aims to identify the risky situations of novice motorcyclists in real roads. Two hundred forty-eight events were recorded and 13 incident scenarios identified. Results revealed that a lack of hazard perception contributed to the majority of these events. The most frequent scenario corresponds to a lane change in dense traffic.     

It Consumerization: Byod-Program Acceptance and its Impact on Employer Attractiveness

Many firms are considering ‘bring-your-own-device’ (BYOD) programs, under which their employees are allowed to bring their own devices to work and use them for both private and business purposes. This study examines what factors determine an employee's intention to participate in a corporate BYOD program and how such programs affect employer attractiveness. We approach our study of acceptance of corporate BYOD programs from the perspective of technology acceptance research. For this purpose, we propose a modified and extended UTAUT model. The model was tested by surveying students in their final term (n = 444). We show that performance expectancies have the strongest positive effect on intention, while perceived threats negatively impact intention. Finally, behavioural intention was positively associated with employer attractiveness, which leads to clear indications for companies considering establishing corporate BYOD programs. BYOD seems to play an increasingly important role in attracting and retaining future talent.     

Achieving traceability in large scale continuous integration and delivery deployment,usage and validation of the eiffel framework

The importance of traceability in software development has long been recognized, not only for reasons of legality and certification, but also to enable the development itself. At the same time, organizations are known to struggle to live up to traceability requirements, and there is an identified lack of studies on traceability practices in the industry, not least in the area of tooling and infrastructure. This paper presents, investigates and discusses Eiffel, an industry developed solution designed to provide real time traceability in continuous integration and delivery. The traceability needs of industry professionals are also investigated through interviews, providing context to that solution. It is then validated through further interviews, a comparison with previous traceability methods and a review of literature. It is found to address the identified traceability needs and found in some cases to reduce traceability data acquisition times from days to minutes, while at the same time alternatives offering comparable functionality are lacking. In this work, traceability is shown not only to be an important concern to engineers, but also regarded as a prerequisite to successful large scale continuous integration and delivery. At the same time, promising developments in technical infrastructure are documented and clear differences in traceability mindset between separate industry projects is revealed.     

Road‐Centered Map‐Aided Localization for Driverless Cars Using Single‐Frequency GNSS Receivers

Accurate localization with high availability is a key requirement for autonomous vehicles. It remains a major challenge when using automotive sensors such as single‐frequency Global Navigation Satellite System (GNSS) receivers, a lane detection camera, and proprioceptive sensors. This paper describes a method that enables the estimation of stand‐alone single‐frequency GNSS errors by integrating the measurements from a forward‐looking camera matched with lane markings stored in a digital map. It includes a parameter identification method for a shaping model, which is evaluated using experimental data. An algebraic observability study is then conducted to prove that the proposed state vector is fully observable in a road‐oriented frame. This observability property is the basis to develop a road‐centered Extended Kalman filter (EKF) that can maintain the observability of every component of the state vector on any road, whatever its orientation. To accomplish this, the filter needs to handle road changes, which it does using bijective transformations. The filter was implemented and tested intensely on an experimental vehicle for driverless valet parking services. Field results have shown that the performance of the estimation process is better than solutions based on EKF implemented in a fixed working frame. The proposed filter guarantees that the drift along the road direction remains bounded. This is very important when the vehicle navigates autonomously. Furthermore, the road‐centered modeling improves the accuracy, consistency, and robustness of the localization solver.