Modeling Intradriver Steering Variability Based on Sensorimotor Control Theories

The purpose of this study is to develop and validate a human-like steering model that can capture, not only the mean, but also the intradriver variability (IDV) of steering behavior, in both routine and emergency scenarios. The IDV model proposed in this study is based on the assumption that steering behavior, in both scenarios, is governed by the same principles as performing point-to-point reaching tasks. The optimal feedback control framework that models the reaching tasks, and the presence of signal-dependent noise in motor commands and sensory feedback, are the mainstays of the proposed model. The driver is assumed to have acquired an internal model of system (muscles, arms, and vehicle) dynamics, and has a preview of the upcoming road. The model is validated using simulator-based data from both routine (curve negotiation) and emergency (obstacle avoidance) scenarios. The IDV model could capture mean steering torque behavior in both routine (variance accounted for (VAF) <inline-formula><tex-math notation="LaTeX">$=$ </tex-math></inline-formula> 92% and emergency (VAF <inline-formula><tex-math notation="LaTeX">$=$</tex-math> </inline-formula> 74% scenarios, but more prominently, it could capture the standard deviation of the steering torque as well, in both routine (VAF <inline-formula><tex-math notation="LaTeX">$=$</tex-math></inline-formula> 83% and emergency (VAF <inline-formula><tex-math notation="LaTeX">$=$</tex-math></inline-formula> 65% scenarios. The promising results show that including signal-dependent noise and modeling steering as a reaching task are steps in the right direction in the field of driver modeling. The model, however, poorly captured the lateral deviation behavior, primarily suspected due to the satisficing behavior exhibited by humans. Developing a nonlinear-iterative version of the IDV model could address the limitations.

[1]  Dean P. Chiang,et al.  Advanced Crash Avoidance Technologies Program – Final Report of the Honda-DRI Team Volume III: Appendix K , 2011 .

[2]  P. Riekert,et al.  Zur Fahrmechanik des gummibereiften Kraftfahrzeugs , 1940 .

[3]  Peter J. Gawthrop,et al.  Intermittent control: a computational theory of human control , 2011, Biological Cybernetics.

[4]  D. Casanova,et al.  A Mathematical Model for Driver Steering Control, with Design, Tuning and Performance Results , 2000 .

[5]  G. Ripaccioli,et al.  Stochastic model predictive control with driver behavior learning for improved powertrain control , 2010, 49th IEEE Conference on Decision and Control (CDC).

[6]  Hong Huang.  Stochastic modelling and control of pension plans , 2000 .

[7]  Ola Benderius,et al.  Evidence for a fundamental property of steering , 2014 .

[8]  D. Whitaker,et al.  Disentangling the Role of Spatial Scale, Separation and Eccentricity in Weber's Law for Position , 1997, Vision Research.

[9]  John A. Michon,et al.  A critical view of driver behavior models: What do we know , 1985 .

[10]  Gustav Markkula,et al.  Modeling driver control behavior in both routine and near-accident driving , 2014 .

[11]  Emanuel V. Todrov.  Studies of goal directed movements , 1998 .

[12]  Philippe Chevrel,et al.  A sensorimotor driver model for steering control , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[13]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[14]  Rob Gray,et al.  A Two-Point Visual Control Model of Steering , 2004, Perception.

[15]  Mark Mulder,et al.  Correct and faulty driver support from shared haptic control during evasive maneuvers , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[16]  Ola Benderius,et al.  Modelling driver steering and neuromuscular behaviour , 2014 .

[17]  Daniel M. Wolpert,et al.  Making smooth moves , 2022 .

[18]  Yasuyoshi Yokokohji,et al.  Design of a Preview Driver Model Based on Optical Flow , 2016, IEEE Transactions on Intelligent Vehicles.

[19]  Emanuel Todorov,et al.  Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System , 2005, Neural Computation.

[20]  Francesco Borrelli,et al.  Robust Predictive Control for semi-autonomous vehicles with an uncertain driver model , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[21]  David J. Cole,et al.  A review of human sensory dynamics for application to models of driver steering and speed control , 2016, Biological Cybernetics.

[22]  Charles C. MacAdam,et al.  Application of an Optimal Preview Control for Simulation of Closed-Loop Automobile Driving , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[23]  David J. Cole,et al.  Development of a novel model of driver-vehicle steering control incorporating sensory dynamics , 2016 .

[24]  Wynn C. Stirling,et al.  Satisficing Revisited , 2000, Minds and Machines.

[25]  Emanuel Todorov,et al.  Optimal control methods suitable for biomechanical systems , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[26]  Ola Benderius,et al.  Comparing and validating models of driver steering behaviour in collision avoidance and vehicle stabilisation , 2014 .

[27]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[28]  A. Galip Ulsoy,et al.  Identification of a Driver Steering Model, and Model Uncertainty, From Driving Simulator Data , 2001, Dynamic Systems and Control.

[29]  David J. Cole,et al.  A Mathematical Model of Driver Steering Control Including Neuromuscular Dynamics , 2008 .

[30]  Daniel Vélez Día,et al.  Biomechanics and Motor Control of Human Movement , 2013 .

[31]  M. Tomizuka.  Optimal continuous finite preview problem , 1975 .

[32]  Günther Prokop,et al.  Modeling Human Vehicle Driving by Model Predictive Online Optimization , 2001 .

[33]  C. A. Burbeck,et al.  Two mechanisms for localization? Evidence for separation-dependent and separation-independent processing of position information , 1990, Vision Research.

[34]  Junmin Wang,et al.  A Driver Steering Model With Personalized Desired Path Generation , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.