Communication and Interaction With Semiautonomous Ground Vehicles by Force Control Steering

While full automation of road vehicles remains a future goal, shared-control and semiautonomous driving--involving transitions of control between the human and the machine--are more feasible objectives in the near term. These alternative driving modes will benefit from new research toward novel steering control devices, more suitably where machine intelligence only partially controls the vehicle. In this article, it is proposed that when the human shares the control of a vehicle with an autonomous or semiautonomous system, a force control, or nondisplacement steering wheel (i.e., a steering wheel which does not rotate but detects the applied torque by the human driver) can be advantageous under certain schemes: tight rein or loose rein modes according to the H-metaphor. We support this proposition with the first experiments to the best of our knowledge, in which human participants drove in a simulated road scene with a force control steering wheel (FCSW). The experiments exhibited that humans can adapt promptly to force control steering and are able to control the vehicle smoothly. Different transfer functions are tested, which translate the applied torque at the FCSW to the steering angle at the wheels of the vehicle; it is shown that fractional order transfer functions increment steering stability and control accuracy when using a force control device. The transition of control experiments is also performed with both: a conventional and an FCSW. This prototypical steering system can be realized via steer-by-wire controls, which are already incorporated in commercially available vehicles.

[1]  Richard Magin,et al.  Can Cybernetics and Fractional Calculus Be Partners?: Searching for New Ways to Solve Complex Problems , 2018, IEEE Systems, Man, and Cybernetics Magazine.

[2]  Natasha Merat,et al.  CityMobil : Human factor issues regarding highly automated vehicles on eLane , 2009 .

[3]  Tim Gordon,et al.  Modeling human lane keeping control in highway driving with validation by naturalistic data , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[4]  Long Cheng,et al.  Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics , 2020, IEEE Transactions on Cybernetics.

[5]  Natasha Merat,et al.  How do Drivers Behave in a Highly Automated Car , 2017 .

[6]  Paul C. Schutte,et al.  The H-Metaphor as a Guideline for Vehicle Automation and Interaction , 2005 .

[7]  Eli Brenner,et al.  Haptic Guidance Needs to Be Intuitive Not Just Informative to Improve Human Motor Accuracy , 2016, PloS one.

[8]  M. P. Smith,et al.  Sidestick controllers for advanced aircraft cockpits , 1992, [1992] Proceedings IEEE/AIAA 11th Digital Avionics Systems Conference.

[9]  Stuart K. Card,et al.  Evaluation of mouse, rate-controlled isometric joystick, step keys, and text keys, for text selection on a CRT , 1987 .

[10]  A. Tustin,et al.  The nature of the operator's response in manual control, and its implications for controller design , 1947 .

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

[12]  I. Podlubny Fractional differential equations : an introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications , 1999 .

[13]  Anna Gerber,et al.  Opengl Programming Guide The Official Guide To Learning Opengl Versions 3 0 And 3 1 , 2016 .

[14]  Mitsuo Kawato,et al.  Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.

[15]  C. B. Gibbs The continuous regulation of skilled response by kinaesthetic feed back. , 1954, The British journal of medical psychology.

[16]  Yu Zhang,et al.  Memory Pattern Identification for Feedback Tracking Control in Human-Machine Systems. , 2019, Human factors.

[17]  B. West Fractional Calculus in Bioengineering , 2007 .

[18]  Xiaowei Gu,et al.  Particle Swarm Optimized Autonomous Learning Fuzzy System , 2020, IEEE Transactions on Cybernetics.

[19]  H. Gomi,et al.  Task-Dependent Viscoelasticity of Human Multijoint Arm and Its Spatial Characteristics for Interaction with Environments , 1998, The Journal of Neuroscience.

[20]  Dawn Song,et al.  Physical Adversarial Examples for Object Detectors , 2018, WOOT @ USENIX Security Symposium.

[21]  Feng Liu,et al.  Common Spatial Pattern Reformulated for Regularizations in Brain–Computer Interfaces , 2020, IEEE Transactions on Cybernetics.

[22]  Ken Perlin,et al.  An image synthesizer , 1988 .

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

[24]  Mark Mulder,et al.  A Topology of Shared Control Systems—Finding Common Ground in Diversity , 2018, IEEE Transactions on Human-Machine Systems.

[25]  Tom Davis,et al.  Opengl programming guide: the official guide to learning opengl , 1993 .

[26]  Lei Shu,et al.  Extended Crossover Model for Human-Control of Fractional Order Plants , 2017, IEEE Access.

[27]  J. Y. C. Chen,et al.  Review of Low Frame Rate Effects on Human Performance , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[28]  Ted Selker,et al.  Force-to-motion functions for pointing , 1990, INTERACT.

[29]  Samy Bengio,et al.  Understanding deep learning requires rethinking generalization , 2016, ICLR.

[30]  Robert S. Olyha,et al.  Negative inertia: a dynamic pointing function , 1995, CHI '95.

[31]  J. Lambert Numerical Methods for Ordinary Differential Systems: The Initial Value Problem , 1991 .

[32]  David A. Abbink,et al.  Shared and cooperative control of ground and air vehicles: Introduction and general overview , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[33]  D. T. McRuer,et al.  HUMAN PILOT DYNAMICS WITH VARIOUS MANIPULATORS. , 1966 .

[34]  J. C. R. Licklider,et al.  Man-Computer Symbiosis , 1960 .

[35]  H. P. Birmingham,et al.  A Design Philosophy for Man-Machine Control Systems , 1954, Proceedings of the IRE.

[36]  Mark Mulder,et al.  Haptic shared control: smoothly shifting control authority? , 2012, Cognition, Technology & Work.

[37]  Effect of muscle tendon vibration on the perception of force , 1985, Experimental Neurology.

[38]  Yu Zhang,et al.  Modeling Lane Keeping by a Hybrid Open-Closed-Loop Pulse Control Scheme , 2016, IEEE Transactions on Industrial Informatics.

[39]  Gustav Markkula,et al.  Evidence Accumulation Account of Human Operators' Decisions in Intermittent Control During Inverted Pendulum Balancing , 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[40]  Masato Abe,et al.  Vehicle Handling Dynamics: Theory and Application , 2009 .

[41]  Bhise,et al.  DRIVER STEERING PERFORMANCE USING JOYSTICK VS. STEERING WHEEL CONTROLS. IN: HUMAN FACTORS IN DRIVING, SEATING AND VISION , 2003 .

[42]  Rieko Osu,et al.  The central nervous system stabilizes unstable dynamics by learning optimal impedance , 2001, Nature.

[43]  Michael J. Griffin,et al.  Driver perception of steering feel , 2007 .

[44]  Kaspar Althoefer,et al.  Salient Feature of Haptic-Based Guidance of People in Low Visibility Environments Using Hard Reins , 2016, IEEE Transactions on Cybernetics.

[45]  C. Marsden,et al.  Frequency peaks of tremor, muscle vibration and electromyographic activity at 10 Hz, 20 Hz and 40 Hz during human finger muscle contraction may reflect rhythmicities of central neural firing , 1997, Experimental Brain Research.