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Title: Methodological aspects of field operational tests of after-market and nomadic driver support systems and impacts on mobility
Authors: Welsh, Ruth
Morris, Andrew
Innamaa, Satu
Keywords: Field operational tests (FOT)
TeleFOT project
Quasi-experimental methods
Information and communication technologies (ICT)
Nomadic devices
Issue Date: 2017
Publisher: Bentham Open © Welsh et al.
Citation: WELSH, R., MORRIS, A. and INNAMAA, S., 2017. Methodological aspects of field operational tests of after-market and nomadic driver support systems and impacts on mobility. The Open Transportation Journal, 11, pp. 90-101.
Abstract: Background: This paper reports on the methodology undertaken and some results achieved within a study of drivers using aftermarket and nomadic devices (the TeleFOT project). Objective: To evaluate the methodology for conducting Field Operational Tests for Information and Communication Technology whilst also providing an example of the method applied in the context of mobility within the TeleFOT project. Method: ‘Top down, bottom up’ approach to the derivation of research questions and hypotheses is described. Statistical analysis has been undertaken on data collected through Field Operational Tests and Travel Diaries considering the impact of information functions (such as navigation, traffic information and green driving) upon journey length. Results: A summary of the results relating specifically to how the length of a journey can be affected by information functions indicates that Navigation and Traffic information can reduce the length of journeys whilst Green Driving functions tend to increase the journey length. Conclusion: The FOT methodology was successfully applied in the TeleFOT project as was the novel method for generating research questions. When turning the theoretical FOT method developed in FESTA into practice, several good innovations were made which and can be recommended for future FOTs; collation of metadata, the use of comparable origin / destination pairs for analysis, centralised processing of raw data into legs in order to simplify the analysis of the huge datasets collected in the project.
Description: This is an Open Access Article. It is published by Bentham Open under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0
Version: Published
DOI: 10.2174/1874447801711010090
URI: https://dspace.lboro.ac.uk/2134/26597
Publisher Link: https://doi.org/10.2174/1874447801711010090
ISSN: 1874-4478
Appears in Collections:Published Articles (Design School)

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