There appears to be a lack of new ideas in driver behavior modeling. Although behavioral research is under some pressure, it seems too facile to attribute this deplorable state of affairs only to a lack of research funds. In my opinion the causal chain may well run in the opposite direction. An analysis of what is wrong has led me to the conclusion that human factors research in the area of driver behavior has hardly been touched by the “cognitive revolution” that swept psychology in the past fifteen years. A more cognitive approach might seem advisable and the “promise of progress” of such an approach should be assessed.

/pdf/a-critical-view-of-driver-behavior-models-what-do-we-know-3v6319x419.pdf

A Critical View of Driver Behavior Models: What Do We Know, What Should We Do?

Summary This paper examines the role of the human driver as the primary control element within the traditional driver-vehicle system. Lateral and longitudinal control tasks such as path-following, obstacle avoidance, and headway control are examples of steering and braking activities performed by the human driver. Physical limitations as well as various attributes that make the human driver unique and help to characterize human control behavior are described. Example driver models containing such traits and that are commonly used to predict the performance of the combined driver-vehicle system in lateral and longitudinal control tasks are identified.

/pdf/understanding-and-modeling-the-human-driver-4i18rkrqa9.pdf

Understanding and modeling the human driver.

Understanding the driver of an automobile has been attractive to researchers from many different disciplines for more than half a century. On the basis of their acquirements, models of the (human) driver have been developed to better understand, analyse and improve the combined couple of driver and automobile. Due to distinctive demands on the models in accordance with different kinds of applications, a variety of driver models is available. An overview of driver models is given with respect to their application and different methodical modelling approaches. The emphasis is put on the interest of engineers, who generally focus on the automobile (like design and optimization of vehicle components and the overall vehicle dynamics behaviour) by applying their approved (mathematical) methods. Nonetheless, a brief look beyond is added to better complete the view on the involved task of driving and driver modelling for automobile dynamics application.

Driver models in automobile dynamics application

Experimental studies show that automobile drivers adjust their speed in curves so that maximum vehicle lateral accelerations decrease at high speeds. This pattern of lateral accelerations is described by a new driver model, assuming drivers control a variable safety margin of perceived lateral acceleration according to their anticipated steering deviations. Compared with a minimum time-to-lane-crossing (H. Godthelp, 1986) speed modulation strategy, this model, based on nonvisual cues, predicts that extreme values of lateral acceleration in curves decrease quadratically with speed, in accordance with experimental data obtained in a vehicle driven on a test track and in a motion-based driving simulator. Variations of model parameters can characterize "normal" or "fast" driving styles on the test track. On the simulator, it was found that the upper limits of lateral acceleration decreased less steeply when the motion cuing system was deactivated, although drivers maintained a consistent driving style. This is interpreted per the model as an underestimation of curvilinear speed due to the lack of inertial stimuli. Actual or potential applications of this research include a method to assess driving simulators as well as to identify driving styles for on-board driver aid systems.

Role of Lateral Acceleration in Curve Driving: Driver Model and Experiments on a Real Vehicle and a Driving Simulator

Much research on driver attention, including evaluations of in-car equipment, at least implicitly assumes that attention is where the gaze is. Research on the dynamics of visual attention, however, suggests that drivers may use peripheral vision and that they learn its use over time, depending on the task demands and eccentricity. To investigate effects of task load and position on lane keeping, 11 novices and 16 experienced drivers were asked to drive along a straight road using only peripheral vision for lane keeping while doing another task foveally. The task varied in position and in mental load, with two difficulty levels in each of two different tasks. In the visual attention tasks, position had a clearly different effect on lane-keeping performance among novices and the experienced, as measured by the distance covered before crossing a lane boundary. Novices' performance deteriorated with the foveal task at near periphery at the speedometer level, whereas the performance of experienced drivers drop...

Maintaining Lane Position with Peripheral Vision during In-Vehicle Tasks

Changes in the design of software algorithms for generating physical motion in flight simulators have typically been put forward on the grounds of improved motion cueing. Little attention has been paid to more practical criteria such as computational cost, ease of adjustment, or evaluation by experienced pilots in a realistic simulation environment. A comparison of three of the algorithms most commonly found in the literature has been performed: classical washout, optimal control, and coordinated adaptive. This consisted of pilot evaluations of these algorithms implemented on a six-degree-of-freedom flight simulator simulating a large transport aircraft during low-altitude flight and ground maneuvering. This paper presents the results of that study from the designer's viewpoint. In it, we contend that, with enough effort, most algorithms can be massaged to perform reasonably well, and that a more important consideration is the ease with which a given algorithm can be brought to high performance levels. If this criterion is used, it appears that the classical algorithm is a good starting point, and that the benefits of an adaptive algorithm can be added gradually to obtain the advantages conferred by nonlinear filtering and "intelligent" cost functions.

Simulator motion-drive algorithms - A designer's perspective

Current motion-drive algorithms have a number of coefficients that are selected to tune the motion of the simulator. Little attention has been given to the process of selecting the most appropriate coefficient values. Final tuning is best accomplished using experienced evaluation pilots to provide feedback to a washout filter expert who adjusts the coefficients in an attempt to satisfy the pilot. This paper presents the development of a tuning paradigm and the capturing of such within an expert system. The focus of this development is the University of Toronto classical algorithm, but the results are relevant to alternative classical and similarly structured adaptive algorithms. This paper provides the groundwork required to develop the tuning paradigm. The necessity of this subjective tuning process is defended. Motion cueing error sources within the classical algorithm are revealed, and coefficient adjustments that reduce the errors are presented.

Motion Washout Filter Tuning: Rules and Requirements

The use of physical motion in flight simulation is still a much debated topic. This paper investigates the more narrow issue of its application in commercial jet transport simulators. We have attempted to quantify the perceptions of airline pilots about the quality of motion possible when a number of different motion-drive algorithms are tested on a simulator employing a state-of-the-art six-degrees-of-freedom motion-base. Four broad categories of algorithms were tested: classical washout, optimal control, coordinated adaptive, and no-motion. It was found that although there was little impact of algorithm type on performance arid control activity, there was a definite effect on how the pilots perceived the simulation environment. Based on these findings, it appears that the coordinated adaptive algorithm is generally preferred by the pilots over the other algorithms tested, there was almost unanimous dislike of the no-motion case.

Response of airline pilots to variations in flight simulator motion algorithms

Concepts for flight simulator motion-drive algorithms range from the most basic to the relatively complex, with little to guide a choice between these, short of implementing them all and choosing the best. To avoid this lengthy process and to put into practice the experience gained in a previous large-scale evaluation exercise, a flexible motion algorithm has been implemented. It can be run as a simple classical algorithm with few free parameters and can be quickly adjusted to yield good motion performance. The more sophisticated adaptive features of the algorithm can then be brought in gradually to improve performance. Various forms of cost functions and adaptive features were formulated and subsequently evaluated on a synergistic 6 degrees-of-freedom motion-base simulator. It was found that a fourth-order cost function coupled with adaptive gain filters yielded the most favorable results. Finally, a supervisory code to ease motion adjustment and to provide a safe interactive interface with the designer is described. This facility permits reduced turnaround time during motion tuning and allows the pilot to experience different motions back-to-back for easier comparison. The supervisory control also allows automatic motion adjustment to different flight conditions. Nomenclature§ aAA

Lloyd D. Reid

Papers

Simulator motion-drive algorithms - A designer's perspective

Motion Washout Filter Tuning: Rules and Requirements

Response of airline pilots to variations in flight simulator motion algorithms

Adaptive Simulator Motion Software with Supervisory Control

A survey of recent driver steering behavior models suited to accident studies