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|Title: ||FESTA. D2.4 Data analysis and modelling|
|Authors: ||Lenard, James|
|Issue Date: ||2008|
|Publisher: ||© FESTA|
|Citation: ||FESTA CONSORTIUM, 2008. FESTA. D2.4 Data analysis and modelling.|
|Abstract: ||The chapter of the handbook and the deliverable on data analysis will provide guidance and
general principles for
- pre-testing to check the usability of the system and the feasibility of the evaluation process,
- controlling the consistency of the chain and the precision with different sampling schemes,
- modelling the impact for each indicators and for an integrated evaluation including a
systemic and multidisciplinary interpretation of the effects,
- integrating and controlling the quality of space-time data from various sources (numerical,
- selecting the appropriate statistical techniques for data processing, PI estimation and
hypothesis testing in accordance to the list of indicators and experimental design,
- scaling up from experimental data and identified models to population and network level.
Experimentalists stress the role and importance of a preliminary field test in FOT. Three main
objectives have been defined to make a preliminary diagnosis of usability of the systems and
to check the relevance and feasibility of the evaluation process. These preliminary tests are
very important for the practical deployment of the FOT as well as for the overall scientific
Recommendations about the monitoring of local and global consistency of the chain of
operations from the database extraction to the hypothesis testing are given, especially to
ensure the validation of the calculation of the Performance indicators.
Integration of the outputs of the different analysis and hypothesis testing requires a kind of
meta-model and the competences of a multidisciplinary evaluation team, specially for
interpretation of the system impact and secondary effects (behavioural adaptation, learning
process, long-term retroaction, …).
In cooperation with WP2.2, methods for data quality control have been defined. Four types of
checks have been defined to complement the information of the data base in order to prepare
the data for the analysis.
Statistical methods have been described for three steps of the chain: data processing, PI
calculation and hypothesis testing. They belong either to exploratory data analysis or to
inferential analysis. Special attention has been given to the precision of the estimates of the
effects or impacts of the system on the Performance indicators by stressing the importance of
controlled randomisation and application of mixed regression models.
Scaling-up relies upon the potential to extrapolate from the PIs to estimates of the impact at
an aggregated level. Three approaches have been defined to carry out the scaling up process
from direct estimations to simulation models with the related assumptions. Models and methodologies for scaling up results on traffic flow, environmental effects (e.g. PM10, CO2,
Noise emissions in db) and traffic safety have been collected.|
|Description: ||Please see the report for a full list of authors. This report is also available at http://www.its.leeds.ac.uk/festa/downloads.pp|
|Publisher Link: ||http://www.its.leeds.ac.uk/festa/downloads.php|
|Appears in Collections:||Official Reports (Design School)|
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