Locus of control

The goal of the present study was to assess the effectiveness of eye blink behavior in measuring drivers’ mental workload. Previous research has shown that when mental workload increases with the primary task difficulty, blink frequency drops. On the opposite, the number of blinks increases when a cognitive secondary task has to be performed concurrently. However, the combined effects of the primary task difficulty and dual-tasking on blink rate have not been investigated. The present study was thus designed to vary systematically both the primary driving task and the cognitive secondary task demand to examine their combined effects on blink rate. The driving task was manipulated by varying the complexity of a simulated driving environment. The cognitive load was manipulated using a concurrent simple reaction time task or a complex calculation task. The results confirmed that eye blink frequency was a sensitive measure to elicit increased mental workload level coming from the driving environment. They also confirmed that blink rate increased with the introduction of a cognitive secondary task while blink duration was not affected. However, eye blink behavior did not provide a clear mental workload signature when driving task demands and dual-task conditions were varied simultaneously. The overall picture goes against the suitability of eye blink behavior to monitor drivers’ states at least when external and internal demands interact.

The effects of driving environment complexity and dual tasking on drivers’ mental workload and eye blink behavior

The last decade has shown an increasing interest on advanced driver assistance systems (ADAS) based on shared control, where automation is continuously supporting the driver at the control level with an adaptive authority. A first look at the literature offers two main research directions: 1) an ongoing effort to advance the theoretical comprehension of shared control, and 2) a diversity of automotive system applications with an increasing number of works in recent years. Yet, a global synthesis on these efforts is not available. To this end, this article covers the complete field of shared control in automated vehicles with an emphasis on these aspects: 1) concept, 2) categories, 3) algorithms, and 4) status of technology. Articles from the literature are classified in theory- and application-oriented contributions. From these, a clear distinction is found between coupled and uncoupled shared control. Also, model-based and model-free algorithms from these two categories are evaluated separately with a focus on systems using the steering wheel as the control interface. Model-based controllers tested by at least one real driver are tabulated to evaluate the performance of such systems. Results show that the inclusion of a driver model helps to reduce the conflicts at the steering. Also, variables such as driver state, driver effort, and safety indicators have a high impact on the calculation of the authority. Concerning the evaluation, driver-in-the-loop simulators are the most common platforms, with few works performed in real vehicles. Implementation in experimental vehicles is expected in the upcoming years.

/pdf/a-review-of-shared-control-for-automated-vehicles-theory-and-1sa68df696.pdf

A Review of Shared Control for Automated Vehicles: Theory and Applications

A large number of haptic driver support systems have been described in the scientific literature. However, there is little consensus regarding the design, evaluation methods, and effectiveness of these systems. This literature survey aimed to investigate: (1) what haptic systems (in terms of function, haptic signal, channel, and supported task) have been experimentally tested, (2) how these haptic systems have been evaluated, and (3) their reported effects on driver performance and behaviour. We reviewed empirical research in which participants had to drive a vehicle in a real or simulated environment, were able to control the heading and/or speed of the vehicle, and a haptic signal was provided to them. The results indicated that a clear distinction can be made between warning systems (using vibrations) and guidance systems (using continuous forces). Studies typically used reaction time measures for evaluating warning systems and vehicle-centred performance measures for evaluating guidance systems. In general, haptic warning systems reduced the reaction time of a driver compared to no warnings, although these systems may cause annoyance. Guidance systems generally improved the performance of drivers compared to non-aided driving, but these systems may suffer from after-effects. Longitudinal research is needed to investigate the transfer and retention of effects caused by haptic support systems.

/pdf/the-effect-of-haptic-support-systems-on-driver-performance-a-5byqow3698.pdf

The Effect of Haptic Support Systems on Driver Performance: A Literature Survey

The aim of this paper is to design and develop an optimal motion cueing algorithm (MCA) based on the genetic algorithm (GA) that can generate high-fidelity motions within the motion simulator’s physical limitations. Both, angular velocity and linear acceleration are adopted as the inputs to the MCA for producing the higher order optimal washout filter. The linear quadratic regulator (LQR) method is used to constrain the human perception error between the real and simulated driving tasks. To develop the optimal MCA, the latest mathematical models of the vestibular system and simulator motion are taken into account. A reference frame with the center of rotation at the driver’s head to eliminate false motion cues caused by rotation of the simulator to the translational motion of the driver’s head as well as to reduce the workspace displacement is employed. To improve the developed LQR-based optimal MCA, a new strategy based on optimal control theory and the GA is devised. The objective is to reproduce a signal that can follow closely the reference signal and avoid false motion cues by adjusting the parameters from the obtained LQR-based optimal washout filter. This is achieved by taking a series of factors into account, which include the vestibular sensation error between the real and simulated cases, the main dynamic limitations, the human threshold limiter in tilt coordination, the cross correlation coefficient, and the human sensation error fluctuation. It is worth pointing out that other related investigations in the literature normally do not consider the effects of these factors. The proposed optimized MCA based on the GA is implemented using the MATLAB/Simulink software. The results show the effectiveness of the proposed GA-based method in enhancing human sensation, maximizing the reference shape tracking, and reducing the workspace usage.

Robust Optimal Motion Cueing Algorithm Based on the Linear Quadratic Regulator Method and a Genetic Algorithm

This paper presents a driving simulation whose aim is twofold: (1) to investigate the possibility of reducing motion clearance to achieve compact and low-cost driving simulators and (2) to evaluate multimodal and immersive virtual reality motion restitution in platooning driving The choice has been made for a driving simulator having at least two degrees of freedom (DOF) These consist of the longitudinal displacement and seat rotations The simulator is also equipped with a force feedback steering wheel for virtual drive assistance These components are gathered on a serial kinematics-type platform to facilitate a control scheme and avoid the architecture complexity A comparative study was made to devise a motion cueing strategy, taking into account both the psychophysical and technological constraints Experimentations were carried out for several case combinations of the longitudinal displacement and seat rotations

/pdf/design-and-control-of-a-small-clearance-driving-simulator-2vbbeycf5d.pdf

Design and Control of a Small-Clearance Driving Simulator

This paper deals with motion control problem for a 2 DOF small driving simulator. The main idea is to test and compare performances of different washout algorithms applied to such platform category. The experimentations allow us to have the best compromise between quality of the perception (sensation), implementation complexity and platform architecture. Implementation of different washout algorithms (optimal, adaptive and classical one) are discussed. Only the longitudinal restitution is studied. The results show that there is not significant differences between these approaches using with platform type. The lack of pitch DOF in our simulator does not allow a restitution of the sustained acceleration and no coordination between longitudinal and pitch channels may be done

/pdf/motion-cueing-algorithms-for-small-driving-simulator-4i9qg48xfv.pdf

Motion cueing algorithms for small driving simulator

Controlling a virtual vehicle is a sensory-motor activity with a specific rendering methodology that depends on the hardware technology and the software in use. We propose a method that computes haptic feedback for the steering wheel. It is best suited for low-cost, fixed-base driving simulators but can be ported to any driving simulator platform. The goal of our method is twofold. 1) It provides an efficient yet simple algorithm to model the steering mechanism using a quadri-polar representation. 2) This model is used to compute the haptic feedback on top of which a tunable haptic augmentation is adjusted to overcome the lack of presence and the unavoidable simulation loop latencies. This algorithm helps the driver to laterally control the virtual vehicle. We also discuss the experimental results that demonstrate the usefulness of our haptic feedback method.

Adaptive Haptic Feedback Steering Wheel for Driving Simulators

This paper deals with motion control problem for a 2 DOF small driving simulator. The main idea is to test and compare performances of different Washout algorithms applied to such platform category. The experimentations allow us to have the best compromise between quality of the human perception, implementation complexity and platform architecture type. Implementation of different washout algorithms (optimal, adaptive and classical one) are discussed. For an objective comparison, the classic algorithm was synthesized so as to take into account the human perception thresholds and the platform workspace limitations. A modelling of a second DOF (seat tilting) is given and simulated to show the inertial effect of the seat movement. Finally, psychophysics study, experimental results and conclusion are given.

/pdf/restitution-movement-for-a-low-cost-driving-simulator-2jpugm2p82.pdf

Restitution movement for a low cost driving simulator

Nowadays, thanks to the improvement of PC technology, it is possible to design high quality visual loop at low cost. Since human factor studies implies a minimal "ecological" immersion, the direct use of ultra low-cost game hardware is not acceptable: the ergonomics of the driving cab and the cues of the various controls (steering-wheel, pedals, gearbox if any...) are insufficiently realistic. Driving simulators have been used for some years for initial training. Many car driving simulators have been designed for that particular purpose. The cab is often representative of an actual one and cues are sometimes acceptable. This kind of tools could be used for research purpose. Unfortunately they are not open to any modification (models, databases, scenarii...) and thus do not allow to undergo experiments. Based upon, in the one hand, INRETS experience in simulator architecture design for human factors studies, and, on the second hand, FAROS experience in the design of low-cost driving simulators for training purpose, our new tool is a good compromise between performance and cost. It is dedicated mainly to research studies. This tool uses FAROS hardware (driving cab) and INRETS electronics and software. A particular emphasis has been put on the development of a haptic feedback steering-wheel . The aim is to help the driver on the fixed-base simulator, thus without any kinestesic feedback, to drive the virtual model. Two modes have been implemented. The first one, based upon a car dynamic model, uses virtual reality techniques coming from teleoperation domain. The second one mixes the previous one with a lane-keeping model. In this paper we introduce the architecture of the simulator and describe the designed steering-wheel haptic feedback system. Then we discuss the various possible uses of the tool. We conclude with perspectives in terms of development. Results of an experiment are also presented.

Hakim Mohellebi

Papers

Design and Control of a Small-Clearance Driving Simulator

Motion cueing algorithms for small driving simulator

Adaptive Haptic Feedback Steering Wheel for Driving Simulators

Restitution movement for a low cost driving simulator

A High Performance/Low-Cost Mini Driving Simulator Alternative for Human Factor Studies