Open AccessRoad Accident Reconstruction Using On-board Data, Especially Focusing on the Applicability in Case of Autonomous Vehicles
Author(s) -
Krisztián Pintér,
Zsolt Szalay,
Gábor Vida
Publication year - 2020
Publication title -
periodica polytechnica. transportation engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 15
eISSN - 1587-3811
pISSN - 0303-7800
DOI - 10.3311/pptr.13469
Subject(s) - event (particle physics) , process (computing) , accident (philosophy) , perspective (graphical) , computer science , european union , liability , engineering , transport engineering , aeronautics , real time computing , artificial intelligence , philosophy , physics , epistemology , finance , quantum mechanics , economics , business , economic policy , operating system
The application of Event Data Recorder (EDR) in passenger cars and vans has been compulsory in the USA since 2014. In the European Union, every passenger car and vehicle manufactured and released must have e-call systems since April 2018. However, neither the data recorded in Event Data Recorders regulated by the current standards nor the data recovered from e-call systems are enough to reconstruct the movements of the vehicle before and after the accident to a degree that the accident could be analyzed in the perspective of liability. The continuous expansion of autonomous vehicle functions – which will inevitably lead to completely autonomous vehicles – makes it particularly justifiable that all vehicles should possess EDR functions and that these data recorders shall store the satisfactory number of parameters for the vehicle's full movement reconstruction.In the article, we will present a process of defining a data package – which will include a definition process for both the data points and the frequency of measuring and recording – that enables the post-event reconstruction of the full motion process, the vehicle movements and the evaluation of liability issues in both regular and irregular operation of autonomous and partially autonomous vehicles.