Participatory design in the development of a smart pedestrian mobility device for urban spaces

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Abstract

Pedestrian mobility is an important component in urban mobility concepts. Walking is a highly flexible means to reach nearby places, to access public transport, or to bridge the “last mile” between the parking space and one’s office or home. Smart pedestrian mobility devices (PMD) can support pedestrians’ activities, either by offering ride-on functions or assistance in everyday activities (e.g., as a carrier for goods) and thereby enhance pedestrians’ connectivity and flexibility. To ensure a high acceptance and adoption rate of PMD, a design approach is needed that explicitly focuses on users’ interests and requirements. We present a multi-level and iterative participatory design approach for the development of smart mobility devices, that reaches from (a) requirement analysis and use case development, (b) communication design, (c) personalization/identity design, (d) exterior design evaluations, to (e) practical driving experience testing. The application and specific suitability of empirical qualitative and quantitative methods is demonstrated and results regarding (a) general acceptance, perceived benefits, barriers, usage conditions and purchase criteria, (b) visual and auditory signal sets for communication design, (c) usability and learnability evaluations after riding on a prototype are presented. The findings demonstrate a high willingness of users to participate in the design process, but also highly differentiated perceptions and requirements regarding a PMD. Even though still in the prototype stage, PMD yield a high potential to serve as a day-to-day mobility assistant (especially for older people) but also as a fun ride-on device (for younger and physically fit people).

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APA

Wilkowska, W., Arning, K., & Ziefle, M. (2017). Participatory design in the development of a smart pedestrian mobility device for urban spaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10290 LNCS, pp. 753–772). Springer Verlag. https://doi.org/10.1007/978-3-319-58640-3_54

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