Driver-Vehicle-Lateraldynamics under Regular Driving Conditions

Mitschke, Manfred

doi:10.1080/00423119308969045

Cited by 12 publications

(10 citation statements)

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“…The ideal driver keeps a previewed point at a certain distance ahead of the vehicle exactly on the required trajectory, see Mitschke (1993). For that propose, the ideal driver steers in an anticipative way according to the curvature at the previewed point and the knowledge on the dynamics of his 'internal vehicle model'.…”

Section: Anticipatory Feed-forward Control Levelmentioning

confidence: 99%

Bicycle Rider Control Modelling for Path Tracking

2015

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Rider models are employed to gain insight into bicycle rider steering behaviour and to improve characteristic properties of bicycles. In this paper, stability properties as well as basic dynamic characteristics of the passive (uncontrolled) bicycle-rider system and consequences on the rider control modelling are addressed. In particular, the unstable motion of the system at low velocities and bandwidth limitations caused by non-minimum phase dynamics are emphasized. To analyse the effectiveness of the steering torque and the lean torque as possible rider's inputs to control the dynamics of the bicycle, a controllability analysis of the bicycle-rider system has been performed. It turns out that lean torque input, in contrast to steering torque input, has marginal impact on the dynamics of the system. Finally, a bicycle rider control model considering human rider properties is presented, and its capabilities are demonstrated by performing a curve entering manoeuvre.

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Section: Anticipatory Feed-forward Control Levelmentioning

confidence: 99%

Bicycle Rider Control Modelling for Path Tracking

2015

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“…The implication is that whenever the system being controlled is changed, the human adapts himself so that the crossover principle is still satisfied. Driving simulator experiments have been performed to verify this fact by Mitschke [26]. Although Mitschke modified vehicle characteristics by changing the vehicle parameters, the same results are effectively achieved using a serial controller in this study.…”

Section: Driver Adaptationmentioning

confidence: 62%

Experimental evaluation of a vehicle steering assist controller using a driving simulator

Chen

Ulsoy

2006

Vehicle System Dynamics

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Human-in-the-loop driving simulator experiments are conducted to evaluate a proposed robust steering assist controller that is designed on the basis of driver uncertainty modelling. A nominal controller (NC) that is designed without consideration of driver model uncertainty is also tested for comparison. Two types of experiments are proposed: a long driving task with nominal configurations and a short driving task with initially large lateral position error. The data are analysed using both time domain and frequency domain metrics. In the time domain, the standard deviation of lateral position error and percentage of road departure are used. In the frequency domain, the stability margins and crossover frequency are used. The driving simulator results indicate that statistically, the designed robust controller shows improvements in the short driving experiments. The improvements in the long driving experiments are less evident because of driver adaptation. The non-robust NC suffers from high gain and should be avoided. The benefits of considering driver model uncertainty in the design of vehicle steering assist controllers are, therefore, justified.

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“…A number of published studies have addressed this problem. Among these, [1], [11], [2], [3] proposed multi-level driver models, sometimes incorporating human behavior, for instance by taking into account human reaction time or by using standard dynamic equations for the vehicle's lateral behavior. [12] presents an inventory of driver models and their application in automobile dynamics.…”

Section: Introductionmentioning

confidence: 99%

“…This study focuses on the structure of the two-level driver models proposed in [1], [11], [2], [3]. Within these models (see Figure 1) the first control is anticipatory, obtained from the standard equation for lateral dynamics in the vehicle bicycle model, such as in [11], [2], and the second is compensatory, making use of PID multi-controllers that correct the lateral deviation and the yaw angle.…”

Section: Introductionmentioning

confidence: 99%

“…Within these models (see Figure 1) the first control is anticipatory, obtained from the standard equation for lateral dynamics in the vehicle bicycle model, such as in [11], [2], and the second is compensatory, making use of PID multi-controllers that correct the lateral deviation and the yaw angle. Multicontrollers is widely used in the literature: for example, [7], [15] designed an adaptive control using multiple models.…”

Section: Introductionmentioning

confidence: 99%

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Steering control based on a two-level driver model: experimental validation and robustness tests

Menhour

Lechner

Charara

2009

2009 IEEE International Conference on Control Applications

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In this article we study a two-level driver model composed of one anticipatory and one compensatory control. The anticipatory control, executed in an open loop, is based mainly on the standard linear equations for the lateral dynamics of the vehicle. The compensatory control, executed in a closed loop, uses N PID controllers for the correction of lateral deviation, and other N PID controllers for the correction of the yaw angle of the vehicle. However, each pair of PID controllers is synthesized on a linear bicycle model (or around an operating point represented by a value of the longitudinal velocity) using the Ziegler-Nichols oscillation method. The different controllers are managed by a switch. We introduce a time delay in the N PID controllers to correct the lateral deviation. We conclude by validating and testing the robustness of the driver model in relation to two different vehicle models: a linear parametervarying model and a nonlinear four-wheel model. Note that the experimental data used here were obtained from a Peugeot 307 laboratory vehicle developed by INRETS-MA.

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Driver-Vehicle-Lateraldynamics under Regular Driving Conditions

Cited by 12 publications

References 1 publication

Bicycle Rider Control Modelling for Path Tracking

Bicycle Rider Control Modelling for Path Tracking

Experimental evaluation of a vehicle steering assist controller using a driving simulator

Steering control based on a two-level driver model: experimental validation and robustness tests

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