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Abstract
This paper presents a new structure for a driving support designed to compensate for the problems caused by the behaviour of the driver without causing a feeling of unease. This assistance is based on a shared control between the human and an automatic support that computes and applies an assisting torque on the steering wheel. This torque is computed from a representation of the hazards encountered on the road by virtual potentials. However, the equilibrium between the relative influences of the human and the support on the steering wheel are difficult to find and depend upon the situation. This is why this driving support includes a modelization of the driver based on an analysis of several face features using a computer vision algorithm. The goal is to determine whether the driver is drowsy or whether he is paying attention to some specific points in order to adapt the strength of the support. The accuracy of the measurements made on the face features is estimated, and the interest of the proposal as well as the concepts raised by such assistance are studied through simulations.
Highlights
After the first appearance of what can be described as an early prototype of a car in 1672 [1], the number of registered vehicles worldwide in 2010 was around 1,500,000,000 [2]
The used method is based on virtual potential fields representing the different hazards that can be encountered on the road
The principle behind and the efficiency of the proposed method are tested through several simulations performed on a driving simulator composed of a steer-by-wire system and a pedal system connected to a computer
Summary
After the first appearance of what can be described as an early prototype of a car in 1672 [1], the number of registered vehicles worldwide in 2010 was around 1,500,000,000 [2]. The purpose of realizing a driving support is to create an assistant able to correctly estimate the danger of a situation and react efficiently. It is possible to realize a temporal switch between freedom and efficiency in the functioning of the estimated state of the driver This assistant must be able to prevent hazardous situations by determining a safe trajectory as well as to wake the driver if he begins to fall asleep. The main innovative aspect of the proposed method is its adaptive behaviour This allows us to solve the equilibrium problem between efficiency and freedom raised by the nature of the active assistant. A temporal switch between these two cases can be done depending upon the state of the driver This assistant combines a potential field approach to represent the danger with a face-features analysis of the user. The proposed support is evaluated using a driving simulator
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