Assessing a Deterministic Model for Autonomous Driving Through Visual Behavior

Abstract

AbstractDriving safety has been improved by automated vehicles, particularly in terms of human error-related accidents, which are considered one of the main causes of traffic accidents. However, despite the increase in the number of sensors, full automation still generates conflictive situations where driver intervention is necessary. Many maneuvers are unique and sometimes unrepeatable, due to the multiple factors involved, being the patterns observation for the development of models and their automation complicated. To achieve greater knowledge of the performance during complex maneuvers on interurban roads, this article proposes the development of a deterministic driving model based on real driving data. The intentional phase prior to the maneuver has been studied in detail thanks to information from the driver’s visual behavior.