Conversing with Our Cars and the Drive for More Aware Experiences, Applying Ambient Theory to Mobile Design
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 14718 LNCS, Page: 298-310
2024
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
This paper considers the application of ambient theory for smart cities to vehicles as an approach to contributing greater understanding to increasingly more aware mobile environments. A review of the research and practice literature for people and car interactions is provided as well as for the use of theory in smart cities, environments, and mobile spaces, enabling formulation of a conceptual framework for more aware driving experiences aided by ambient theory. Methodologically, an exploratory case study approach is employed combined with an explanatory correlational design in operationalizing the conceptual framework formulated for use in this paper. Variables of interest such as sharing and access to public data are identified and assessed in relation to awareness, in search of patterns and relationships. Findings also emerge for awareness through online conference polling and in relation to the everyday driving experience, employed to gain insight into vehicular conversing and interacting. Limitations, challenges, and opportunities are identified giving rise to rich spaces for debate and exploration among vehicle manufactures; software developers; urban researchers, practitioners, and planners; and community members going forward.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85195867456&origin=inward; http://dx.doi.org/10.1007/978-3-031-59988-0_18; https://link.springer.com/10.1007/978-3-031-59988-0_18; https://dx.doi.org/10.1007/978-3-031-59988-0_18; https://link.springer.com/chapter/10.1007/978-3-031-59988-0_18
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know