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Titel:

Analyzing Human Driving Data - An Approach Motivated by Data Science Methods

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Wagner, P.; Niepold, R.; Gabloner, S.; Margreiter, M.
Abstract:
By analyzing a large data-base of car-driving data in a generic way, a few elementary facts on car-following have been found out. The inferences stem from the application of the mutual information to detect correlations to the data. Arguably, the most interesting fact is that the acceleration of the following vehicle depends mostly on the speed-difference to the lead vehicle. This seems to be a causal relationship, since acceleration follows speed-difference with an average delay of 0.5 s. Furth...     »
Zeitschriftentitel:
Journal Chaos, Solitons & Fractals
Jahr:
2016
Jahr / Monat:
2016-03
Monat:
Mar
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1016/j.chaos.2016.02.008
WWW:
https://www.researchgate.net/publication/296693379_Analyzing_human_driving_data_an_approach_motivated_by_data_science_methods
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