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Detecting deviation from normal driving using SHRP2 NDS data
conference contribution
posted on 2017-03-02, 12:04 authored by E. Papazikou, Mohammed Quddus, Pete ThomasNormal driving is naturally the first stage of the crash development sequence. Investigating normal driving can be proved useful for comparisons with safety critical scenarios and also crash prevention. The better we understand it, the more effectively we can detect deviations and stop them before they culminate in crashes. This study utilises Naturalistic driving data from the Strategic Highway Research Program 2 (SHRP2) to look into normal driving
scenarios. Indicators’ thresholds were assumed with influence by the literature and then the values were validated based on real world data. The paper focuses on the methodology for deriving indicators representative of baseline, uneventful driving. With the approach that is
presented here, reliable thresholds for variables can be introduced, capable of detecting the deviation on its very early onset.
Funding
This paper was sponsored by TRB committee AND30 Standing Committee on Simulation and Measurement of Vehicle and Operator Performance. We wish to express special thanks to Insurance Institute for Highway Safety (IIHS-HLDI) for their financial support with which the SHRP2 NDS data was obtained.
History
School
- Design
Published in
Transportation Research Board 2017Citation
PAPAZIKOU, E., QUDDUS, M.A. and THOMAS, P., 2017. Detecting deviation from normal driving using SHRP2 NDS data. Presented at the Transportation Research Board (TRB) 96th Annual Meeting, Washington D.C., US, 8th-12th January 2017.Publisher
© The AuthorsVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2016-08-01Publication date
2017Notes
This is a conference paper.Publisher version
Book series
TRB 96th Annual Meeting Compendium of Papers;17-03309Language
- en