Text size
  • Small
  • Medium
  • Large
Contrast
  • Standard
  • Blue text on blue
  • High contrast (Yellow text on black)
  • Blue text on beige

    An Empirical Framework for Understanding Human-Technology Interaction Optimisation for Route Planning

    HCI 2018

    Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018)

    Belfast, UK, 4 - 6 July 2018

    AUTHORS

    Genovefa Kefalidou

    ABSTRACT

    http://dx.doi.org/10.14236/ewic/HCI2018.62

    A number of interactive systems have been developed in the past to simulate or improve optimised route planning as part of problem solving (e.g. Vehicle Routing Problems (VRPs)) focussing mainly in the utilisation of computational algorithms. Main reasons for developing such interactive systems is that they combine the strengths both computerised systems and humans have, to aid the generation of optimal solutions and promote green logistics. Under a joint-cognitive perspective, the system and the human operator (user) become parts of a single ecosystem, cooperating to complete a task and in which cognitive technologies aid them to reach a decision.

    This paper reports the performance-based design of such an interactive tool that supports optimisation in route planning. It aims to identify human performance, behaviour and opportunities for designing innovative user-centred interactive optimisation tools for route planning. Twenty-six users evaluated the interactive route planner. Results suggest that switching strategies while planning routes lead to increase in route optimality while providing different levels of control for the user. Results lead to the extension of a joint-cognitive approach framework for optimisation routing problems that takes into account both performance metrics and contextual factors such as changes within the task environment. Related implications to optimisation systems’ design and evaluation are also discussed with a particular focus on how new ubiquitous navigation technologies can be improved to promote co-operation and more optimal route planning.

    PAPER FORMATS

    PDF filePDF Version of this Paper (854kb)