This paper presents results from a series of focus groups, aimed at enhancing technical engineering system requirements, for a public transport system, encompassing a fleet of platooning low-speed autonomous vehicles (LSAV; aka pods) in urban areas. A critical review of the pods was conducted, as part of a series of technical workshops, to examine the key areas of the system that could affect users and other stakeholders, such as businesses and the public. These initial findings were used to inform a series of focus groups, aimed at identifying the public's views of multiple autonomous vehicles being deployed in a pedestrianised area that can join and form platoons. Analysis of findings from the focus groups suggests that while people view platooning public transport vehicles favourably as a passenger, they have some concerns from a pedestrian perspective. Thematic analysis was applied to these findings and a systematic approach was used to identify where subjective outputs could be formalised to inform requirements. Finally, a step-by-step requirements elicitation process is presented that illustrates the method used to convert qualitative user data to objective engineering requirements.
|Title of host publication||2019 IEEE Intelligent Vehicles Symposium, IV 2019|
|Number of pages||6|
|Publication status||Published - 29 Aug 2019|
|Event||2019 IEEE Intelligent Vehicles Symposium - Paris, France|
Duration: 9 Jun 2019 → 12 Jun 2019
Conference number: 30
|Name||IEEE Intelligent Vehicles Symposium, Proceedings|
|Conference||2019 IEEE Intelligent Vehicles Symposium|
|Period||9/06/19 → 12/06/19|
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ASJC Scopus subject areas
- Computer Science Applications
- Automotive Engineering
- Modelling and Simulation
Woodman, R., Lu, K., Higgins, M. D., Brewerton, S., Jennings, P., & Birrell, S. (2019). A Human Factors Approach to Defining Requirements for Low-speed Autonomous Vehicles to Enable Intelligent Platooning. In 2019 IEEE Intelligent Vehicles Symposium, IV 2019 (pp. 2371-2376).  (IEEE Intelligent Vehicles Symposium, Proceedings). IEEE. https://doi.org/10.1109/IVS.2019.8814128