Jean-Christophe Popieul

Using driver's head movements evolution as a drowsiness indicator

Many studies have been conducted to try to put forward measurable indicators that could help in the design of alerting devices used to reliably monitor severe driver drowsiness. However, most of these indicators are either too sensitive to environment modifications (performance indicators), invasive for the driver (EEG, EOG...) or are complex and expensive to measure (Eye blinks, PERCLOS...). This study aims at proposing a set of indicators related to driver performance and physiology that could be efficient for monitoring driver drowsiness and be easy to measure. Thirty two subjects took part to a long duration simulated highway trip (336 km) during which performance and physiological data were recorded The analysis of these data puts forward two sets of indicators : firstly, a set of performance indicators whose evolutions are consistent with those described in literature. They ensure the detection of drowsiness during the experiment. Secondly, a set of physiological indicators : the head movements dispersion. This has revealed itself to be a very good indicator as it evolves in the same way as the performance ones on long lasting periods while being poorly influenced by the road environment, contrary to most performance indicators.

Toward a Shared Lateral Control Between Driver and Steering Assist Controller

Abstract Future driving assistance systems must be designed in order to guarantee a smooth steering control action of the controller continuously, considering the driver in-the-loop and without generating negative interference. This paper proposes the design of a shared lateral control in the framework of the active safety systems that integrates the coordination of the authority between human driver and automatic copilot. The vehicle steering assist controller is designed using a driver model in order to take into account the drivers intentions in particular during curve negotiation. This approach minimizes controller intervention while the driver is awake and steers correctly. To reduce the complexity in control computations, a simplified linear combination of the system state is determined via an optimal control by solving a Linear Quadratic Regulator (LQR) problem. A decision making algorithm for the control authority shifting between the driver and the electronic copilot is implemented and the trade-off between the accuracy of lane following and ratio of system interference is investigated.

Cooperative Steering Assist Control System

The paper deals with the design of lateral shared vehicle control taking into account the interaction between the driver and the assistance system. The shared control system is designed in such a way to ensure a good transfer of the control authority without generating negative interference. For that a driver model that allows making valid predictions on the driver behaviour is integrated in the design process of the controller. In order to avoid complex conflict situations such as during lane change maneuver, a decision making algorithm for the control authority shifting is also proposed and implemented. Experimental results provided in the paper, using interactive simulator, show the effectiveness of the approach to ensure shared lateral vehicle control.

LMI-based control synthesis of constrained Takagi-Sugeno fuzzy systems subject to L 2 or L ∞ disturbances

This paper is devoted to the development of a new saturated non-parallel distributed compensation control law for disturbed Takagi-Sugeno fuzzy systems subject to both control input and state constraints. In order to cover a large range of real-world applications, both L 2 and L ∞ disturbances are considered which result in two different control design procedures. A parameter-dependent version of the generalized sector condition is effectively exploited in a fuzzy Lyapunov control framework to handle the control input saturation. Moreover, the proposed control method is based on the concept of robust invariant set which is able to provide an explicit characterization of the estimated domain of attraction of the closed-loop system. Different optimization algorithms are also proposed to deal with the trade-off between different closed-loop requirements in a local control context. The design conditions are expressed in terms of linear matrix inequalities which can be solved efficiently with available solvers. The numerical examples illustrate how the proposed methodology leads to less conservative results as well as less computational complexity when compared to very recent works in the literature.

Driver-Automation Cooperative Approach for Shared Steering Control Under Multiple System Constraints: Design and Experiments

This paper addresses the shared lateral control between a human driver and a lane keeping assist system of intelligent vehicles for both lane keeping and obstacle avoidance. This control issue is very challenging in todays automotive industry due to the human–machine interaction involved in the control design. In this paper, we propose a new approach to consider such an interaction via a fictive driver activity parameter introduced into the road–vehicle system. Hence, the steering assistance actions can be computed according to the drivers real-time behaviors. The Takagi–Sugeno fuzzy control approach is proposed to deal with the time-varying driver activity parameter and vehicle speed. Especially, the concept of robust invariant set is exploited using Lyapunov arguments to handle theoretically both system state and control input limitations. Considering these system constraints in the control design procedure aims to improve the drivers safety and comfort. Experimental tests with a human driver and an advanced interactive dynamic driving simulator are conducted to show the effectiveness of the proposed method.

Human-Machine Interaction in Automated Vehicle: The ABV Project

Abstract The work described in this paper is part of a research program named ABV (Low Speed Automation) where the goal is the automation of road vehicle at low speed while ensuring the sharing of driving between the driver and the assistance. This paper focuses on the problem of human-machine cooperation in the specific context of vehicle driving, with a view of shared control between driver and automation, considering the acceptability of the system and the driver distractions and drowsiness.

Cooperating with an assistance tool for safe driving

Abstract The LAMIH particularly the research group Human-Machine Systems, has studied human-machine cooperation for many years, in a variety of contexts where safety is essential. Our approach is multi-disciplinary and uses different models and methods to elaborate symbolic and formal representations of human-machine cooperation. Our principal objective is to propose and evaluate a semi-formal framework for modeling cooperative activities between human or artificial agents, each of which has a different level of ability, reliability or adaptability. In the present study, human-machine cooperation was analyzed in order to define and evaluate a system capable of taking the full control of an automobile so as to avoid traffic accidents.

Fuzzy Segmentation for the Exploratory Analysis of Multidimensional Signals: Example From a Study on Driver Overtaking Behavior

This paper explains the key role played by windowing in the preliminary analysis of multifactor and multivariate (MFMV) databases. The explanation is based on the general case of a database featuring quantitative or qualitative measurement variables and a hyperparallelepipedic structure in which the directions correspond to the factors. In order to maintain the MFMV aspects of this data structure, the windowing approach as described in this paper does not reduce the information as much as most of the basic non-windowing summarizing procedures using the standard statistical indicators. First, the data in each cell of the hyperparallelepiped are transformed into membership values that can be averaged over factors, such as time or individuals. Then, these membership values may be potentially investigated into with several graphic techniques; for this paper, multiple correspondence analysis (MCA) was chosen. The presentation fall into two parts. First, a didactic example based on a simulated data set describes the approach in comparison with more traditional approaches, and then a real data set, with multidimensional signals recorded for 34 subjects in 15 experimental overtaking situations, is used to demonstrate the power of the “space windowing/MCA” pair on a large real database. Next, the discussion section weighs out the pros and the cons of using space windowing to perform a preliminary analysis of a large MFMV database in studies of human component systems.

From classic statistical characterization to fuzzy windowing based characterization for the exploratory analysis of miscellaneous time variables: example in the field of car driving studies

The problem of data characterization of quantitative and qualitative measurement scales is stated in the context of an exploratory multivariate statistical analysis. An example from a car driving study is considered where the quantitative data correspond to the car and head movements, while the qualitative data correspond to objects being viewed--road, bridge, sign-post, etc. For each of these two sets, the literature is analyzed first in terms of data characterizing methods and relationship obtaining methods. Then we propose to evaluate and compare nine quantitative data characteriing methods: five corresponding to classic statistical indicators, two to crisp space windowing with either two or three windows, and two on fuzzy windowing with either two or three windows. Logically the last method appears as the best (according to our evaluation procedure). Then we propose a bidimensional fuzzy windowing instead of a crisp one to characterize the gaze positions. Finally the multiple correspondence analysis is used to investigate the membership value averages obtained from the characterization stage.

Multi-level cooperation between the driver and an automated driving system during lane change maneuver

This article presents an automated driving system that ensures cooperation with the driver. The system architecture is structured in hierarchical levels to allow suitable interaction with the driver on multiple driving levels. A multi-level cooperative interaction concept is developed to continuously share control and dynamically manage interferences and decision authority between the driver and the system according to the situation. The system extends the lane keeping function with an active lane change assistance function. The necessary components for the multi-level cooperation concept are presented and experimental results show a good and intuitive interaction for active lane change assistance.