26 research outputs found
Trust in an autonomously driven simulator and vehicle performing maneuvers at a T-junction with and without other vehicles
Autonomous vehicle (AV) technology is developing rapidly. Level 3 automation assumes the user might need to respond to requests to retake control. Levels 4 (high automation) and 5 (full automation) do not require human monitoring of the driving task or systems [1]: the AV handles driving functions and makes decisions based on continuously updated information. A gradual switch in the role of the human within the vehicle from active controller to passive passenger comes with uncertainty in terms of trust, which will likely be a key barrier to acceptability, adoption and continued use [2]. Few studies have investigated trust in AVs and these have tended to use driving simulators with Level 3 automation [3, 4]. The current study used both a driving simulator and autonomous road vehicle. Both were operating at Level 3 autonomy although did not require intervention from the user; much like Level 4 systems. Forty-six participants completed road circuits (UK-based) with both platforms. Trust was measured immediately after different types of turns at a priority T-junction, increasing in complexity: e.g., driving left or right out of a T-junction; turning right into a T-junction; presence of oncoming/crossing vehicles. Trust was high across platforms: higher in the simulator for some events and higher in the road AV for others. Generally, and often irrespective of platform, trust was higher for turns involving an oncoming/crossing vehicle(s) than without traffic, possibly because the turn felt more controlled as the simulator and road AVs always yielded, resulting in a delayed maneuver. We also found multiple positive relationships between trust in automation and technology, and trust ratings for most T-junction turn events across platforms. The assessment of trust was successful and the novel findings are important to those designing, developing and testing AVs with users in mind. Undertaking a trial of this scale is complex and caution should be exercised about over-generalizing the findings
Meeting the cultural and service needs of Arabic international students by using QFD
Quality has become an important factor in global competition for many reasons. Intensive global competition and the demand for better quality by customers has led organizations to realize the benefits of providing quality products and services in order to successfully compete and survive. Higher education institutions are one example of these organisations. Higher education institutions work in an intensive competitive environment worldwide driven by increasing demands for learning by local and international students. As a result, the managers of these sectors have realized that improving the quality of services is important for achieving customer satisfaction which can help survival in an internationally competitive market. To do this, it is necessary for organizations to know their customers and identify their requirements. To this end, many higher education institutions have adopted principles of total quality management (TQM) to improve their education quality which leads to better performance through involvement of every department to achieve excellence in business. This chapter considers the importance of measuring quality in order to assist universities to proactively manage the design and improvement of the social and academic experiences of postgraduate international students, and plan management decision-making processes to deliver high-quality services in a globalized business of provision of higher education. Higher education institutions must operate effectively and efficiently and be able to deliver quality programs, by seeking to better understand the needs of their customers to be competitive in this market space
A comparative study: use of a Brain-computer Interface (BCI) device by people with cerebral palsy in interaction with computers
Computing the divisional cost of capital using the pure-play method
The cost of capital model is used to calculate the net present value (NPV) of projects within a multi-unit corporation but may provide incorrect answers for projects that have a level of risk that differs from the overall average risk level for the corporation. We demonstrate the use of the pure-play method for calculating the required rate of return for a division of a corporation that has risk characteristics that differ from the risk characteristics of the overall corporation. We apply this methodology to the Integrated Electronic Systems Segment (IESS) of the Motorola Corporation. We find that the IESS division cost of capital of is 9.3% rather than the 12.3% cost of capital for the corporation as a whole.
The Relevance Of Theory To Human-Robot Teaming Research And Development
In many disciplines and fields, theories help organize the body of knowledge in the field and provide direction for research. In turn, research findings contribute to theory building. The field of human-robot teaming (HRT) is a relatively new one, spanning only over the last two decades. Much of the research in this field has been driven by expediency rather than by theory, and relatively little effort has been invested in using HRT research to advance theory. As the field of HRT continues to expand rapidly, we find it increasingly necessary to relate theories to the research so that one can inform the other. As an initial effort, the current work will discuss and evaluate two broad research areas in human-robot teaming, and identify theories relevant to each area. The areas are (i) human-robot interfaces, and (ii) specific factors that enable teaming. In identifying the relevant theories for each area, we will describe how the theories were used and if findings supported the theories