Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/127793
Title: Semi-autonomous vehicles: Usage-based data evidences of what could be expected from eliminating speed limit violations
Author: Pérez Marín, Ana María
Guillén, Montserrat
Keywords: Risc (Assegurances)
Assegurances d'automòbils
Seguretat viària
Automatització
Primes (Assegurances)
Risk (Insurance)
Automobile insurance
Traffic safety
Automation
Insurance premiums
Issue Date: Feb-2019
Publisher: Elsevier
Abstract: The use of advanced driver assistance systems and the transition towards semi-autonomous vehicles are expected to contribute to a lower frequency of motor accidents and to have a significant impact for the automobile insurance industry, as rating methods must be revised to ensure that risks are correctly measured. Telematics information and usage-based insurance research are analyzed to identify the effect of driving patterns on the risk of accident. This is used as a starting point for addressing risk quantification and safety for vehicles that can control speed. The effect of excess speed on the risk of accidents is estimated with a real telematics data set. Scenarios for a reduction of speed limit violations and the consequent decrease in the expected number of accident claims are shown. If excess speed could be eliminated, then the expected number of accident claims could be reduced to half of its initial value, applying the average conditions of the data used in this study. As a consequence, insurance premiums also diminish.
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.aap.2018.11.005
It is part of: Accident Analysis and Prevention, 2019, vol. 123, num. February, p. 99-106
URI: http://hdl.handle.net/2445/127793
Related resource: https://doi.org/10.1016/j.aap.2018.11.005
ISSN: 0001-4575
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

Files in This Item:
File Description SizeFormat 
685079.pdf235.6 kBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons