1) Background: Data collection procedures allow to obtain harmonization of in-depth road accident databases. Plausibility of calculable accident-related kinematic parameters depends on the constraints imposed on calculation, making their uncertainty degree higher than the one for measurable parameters (i.e., traces, airbag activation, etc.). Uncertainty translates in information loss, making the statistics based on databases analysis less consistent. Since kinematic parameters describe the global accident dynamics, their correctness assessment has a fundamental importance; (2) Methods: the paper takes as reference data collected in the Initiative for the GLobal harmonisation of Accident Data (IGLAD) database for vehicle-to-vehicle crashes. The procedure, however, has general nature and applies identically for other databases and multiple impacts between vehicles. To highlight issues which can arise in accident-related data collection, 3 different checks are proposed for parameters correctness assessment; (3) Results: by 4 examples, 1 with correct and 3 with incorrect parameters reported, the paper demonstrates that errors can go beyond simple calculation uncertainty, implying that a deeper analysis is desirable in data collection; (4) Conclusions: the step-by-step guidelines described in this paper will help in increasing goodness of collected data, providing for a methodology which can be used by each individual involved in accident data collection, both for collection itself and subsequent verification analysis.

Vehicle Accident Databases: Correctness Checks for Accident Kinematic Data / D. Vangi, C. Cialdai, Michelangelo-Santo Gulino, Kjell Gunnar Robbersmyr. - In: DESIGNS. - ISSN 2411-9660. - ELETTRONICO. - 2018:(2018), pp. 0-0. [10.3390/designs2010004]

Vehicle Accident Databases: Correctness Checks for Accident Kinematic Data

D. Vangi;C. Cialdai;GULINO, MICHELANGELO-SANTO
;
2018

Abstract

1) Background: Data collection procedures allow to obtain harmonization of in-depth road accident databases. Plausibility of calculable accident-related kinematic parameters depends on the constraints imposed on calculation, making their uncertainty degree higher than the one for measurable parameters (i.e., traces, airbag activation, etc.). Uncertainty translates in information loss, making the statistics based on databases analysis less consistent. Since kinematic parameters describe the global accident dynamics, their correctness assessment has a fundamental importance; (2) Methods: the paper takes as reference data collected in the Initiative for the GLobal harmonisation of Accident Data (IGLAD) database for vehicle-to-vehicle crashes. The procedure, however, has general nature and applies identically for other databases and multiple impacts between vehicles. To highlight issues which can arise in accident-related data collection, 3 different checks are proposed for parameters correctness assessment; (3) Results: by 4 examples, 1 with correct and 3 with incorrect parameters reported, the paper demonstrates that errors can go beyond simple calculation uncertainty, implying that a deeper analysis is desirable in data collection; (4) Conclusions: the step-by-step guidelines described in this paper will help in increasing goodness of collected data, providing for a methodology which can be used by each individual involved in accident data collection, both for collection itself and subsequent verification analysis.
2018
2018
0
0
D. Vangi, C. Cialdai, Michelangelo-Santo Gulino, Kjell Gunnar Robbersmyr
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1143800
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