Understanding High-Skilled Driving Through Tire Utilization Characteristics: A Driver-in-the-Loop Vehicle Dynamics Perspective

Ilhan Lee; Jaewon Nah

doi:10.22680/kasa2026.18.3.087

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2026 Vol.18, Issue 3 Preview Page Next Page

Understanding High-Skilled Driving Through Tire Utilization Characteristics: A Driver-in-the-Loop Vehicle Dynamics Perspective

30 September 2026. pp. 87-103

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Abstract

Highly skilled drivers can operate vehicles near handling limits even though tire forces, road friction, and many vehicle states are not directly observable. This study adopts a driver-in-the-loop vehicle dynamics perspective to interpret high-skilled driving through tire utilization characteristics. The objective is not to estimate individual tire forces or reproduce driving trajectories, but to examine how available vehicle dynamic capability is utilized and reflected in observable vehicle-level responses. Vehicle trajectories, speed profiles, longitudinal and lateral acceleration, and g-g diagrams are analyzed. The relationship between the friction circle and the g-g diagram is used as an interpretive basis, while an empirical tire utilization envelope is employed only as a qualitative reference. A pilot study was conducted using driving data from three professional drivers with different performance levels under similar conditions. Representative sequential corner sections were selected to examine differences in trajectory, speed management, acceleration transition, and g-g characteristics. The results indicate that the performance difference was not sufficiently explained by minimum corner speed, maximum lateral acceleration, or peak values in g-g space. The higher-performance driver did not simply use a larger acceleration envelope. The main difference was observed during the transition to re-acceleration, where lateral tire utilization was reduced and positive longitudinal acceleration was recovered more effectively. These observations suggest that tire utilization characteristics can help interpret high-skilled driving as a temporal process of organizing vehicle dynamic capability. The proposed perspective may support studies on driver coaching, human-inspired vehicle control, expert driver modeling, and learning from skilled human operators for intelligent machines, including collaborative and humanoid robots.

Keywords

Driver-in-the-Loop

Vehicle Dynamics

Tire Utilization

High-Skilled Driver

Driver Behavior Modeling

References

Ericsson, K. A., Krampe, R. T. and Tesch-Römer, C., 1993, “The Role of Deliberate Practice in the Acquisition of Expert Performance,” Psychological Review, Vol. 100, No. 3, pp. 363~406.

10.1037/0033-295X.100.3.363

Seo, D., Chae, H. and Yi, K., 2023, “Human Driving Data Based Simulation Tool to Develop and Evaluate Automated Driving Systems’ Lane Change Algorithm in Urban Congested Traffic,” Journal of Auto-vehicle Safety Association, Vol. 15, No. 2, p. 21.

Shadmehr, R. and Mussa-Ivaldi, F. A., 1994, “Adaptive Representation of Dynamics During Learning of a Motor Task,” Journal of Neuroscience, Vol. 14, No. 5, pp. 3208~3224.

10.1523/JNEUROSCI.14-05-03208.19948182467PMC6577492

Wolpert, D. M. and Flanagan, J. R., 2001, “Motor Prediction,” Current Biology, Vol. 11, No. 18, pp. R729~R732.

10.1016/S0960-9822(01)00432-8

Kawato, M., 1999, “Internal Models for Motor Control and Trajectory Planning,” Current Opinion in Neurobiology, Vol. 9, No. 6, pp. 718~727.

10.1016/S0959-4388(99)00028-8

Oulasvirta, A., Normoyle, A., Gentner, D., Khamis, M. and Hornbæk, K., 2022, “Computational Rationality as a Theory of Interaction,” Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1~14.

10.1145/3491102.3517739

Donges, E., 1978, “A Two-Level Model of Driver Steering Behavior,” Human Factors, Vol. 20, No. 6, pp. 691~707.

10.1177/001872087802000607

McRuer, D. T. and Krendel, E. S., 1974, “Mathematical Models of Human Pilot Behavior,” AGARD-AG-188, Advisory Group for Aerospace Research and Development, pp. 1~46.

Salvucci, D. D., 2006, “Modeling Driver Behavior in a Cognitive Architecture,” Human Factors, Vol. 48, No. 2, pp. 362~380.

10.1518/001872006777724417

Negash, N. M. and Yang, J., 2023, “Driver Behavior Modeling Toward Autonomous Vehicles: Comprehensive Review,” IEEE Access, Vol. 11, pp. 22788~22821.

10.1109/ACCESS.2023.3249144

Yuan, Y., Wang, X., Calvert, S., Happee, R. and Wang, M., 2024, “A Risk-Based Driver Behaviour Model,” IET Intelligent Transport Systems, Vol. 18, No. 1, pp. 88~100.

10.1049/itr2.12435

Van Leeuwen, P. M., De Groot, S., Happee, R. and De Winter, J. C., 2017, “Differences Between Racing and Non-Racing Drivers: A Simulator Study Using Eye-Tracking,” PLoS ONE, Vol. 12, No. 11, e0186871.

10.1371/journal.pone.018687129121090PMC5679571

Wintersberger, P., Frison, A. K., Riener, A. and Weigl, K., 2020, “Let Me Finish Before I Take Over: Towards Attention Aware Device Integration in Highly Automated Vehicles,” Proceedings of the 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI), pp. 53~65.

10.1145/3239060.3239085

Plebe, A., Svensson, H., Mahmoud, S. and Da Lio, M., 2024, “Human-Inspired Autonomous Driving: A Survey,” Cognitive Systems Research, Vol. 83, Article 101169.

10.1016/j.cogsys.2023.101169

Li, A., Jiang, H., Li, Z., Zhou, J. and Zhou, X., 2019, “Human-Like Trajectory Planning on Curved Road: Learning from Human Drivers,” IEEE Transactions on Intelligent Transportation Systems, Vol. 21, No. 8, pp. 3388~3397.

10.1109/TITS.2019.2926647

Abbink, D. A., Carlson, T., Mulder, M., de Winter, J. C. F., Aminravan, F., Gibo, T. L. and Happee, R., 2018, “A Topology of Shared Control Systems—Finding Common Ground in Diversity,” IEEE Transactions on Human-Machine Systems, Vol. 48, No. 5, pp. 509~525.

10.1109/THMS.2018.2791570

Rajamani, R., 2012, Vehicle Dynamics and Control, 2nd Ed., Springer, New York.

10.1007/978-1-4614-1433-9

Pacejka, H. B., 2012, Tire and Vehicle Dynamics, 3rd Ed., Butterworth-Heinemann, Oxford.

Gustafsson, F., 1997, “Slip-Based Tire-Road Friction Estimation,” Automatica, Vol. 33, No. 6, pp. 1087~1099.

10.1016/S0005-1098(97)00003-4

Baffet, G., Charara, A. and Lechner, D., 2009, “Estimation of Vehicle Sideslip, Tire Force and Wheel Cornering Stiffness,” Control Engineering Practice, Vol. 17, No. 11, pp. 1255~1264.

10.1016/j.conengprac.2009.05.005

Nah, J., Seo, J., Yi, K., Kim, W. and Lee, J., 2015, “Friction Circle Estimation-Based Torque Distribution Control of Six-Wheeled Independent Driving Vehicles for Terrain-Driving Performance,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 229, No. 11, pp. 1469~1482.

10.1177/0954407014564780

Cha, H., Kim, J., Yi, K. and Park, J., 2024, “Investigation into High-Performance Tire Characteristics at the Limits of Handling,” Vehicle System Dynamics, Vol. 62, No. 2, pp. 428~447.

10.1080/00423114.2023.2176326

Williams, A. M. and Davids, K., 1998, “Visual Search Strategy, Selective Attention, and Expertise in Soccer,” Research Quarterly for Exercise and Sport, Vol. 69, No. 2, pp. 111~128.

10.1080/02701367.1998.10607677

Franklin, D. W. and Wolpert, D. M., 2011, “Computational Mechanisms of Sensorimotor Control,” Neuron, Vol. 72, No. 3, pp. 425~442.

10.1016/j.neuron.2011.10.006

Shadmehr, R., Smith, M. A. and Krakauer, J. W., 2010, “Error Correction, Sensory Prediction, and Adaptation in Motor Control,” Annual Review of Neuroscience, Vol. 33, pp. 89~108.

10.1146/annurev-neuro-060909-153135

Information

Publisher :Korean Auto-vehicle Safety Association
Publisher(Ko) :한국자동차모빌리티안전학회
Journal Title :Journal of Auto-vehicle Safety Association
Journal Title(Ko) :자동차안전학회지
Volume : 18
No :3
Pages :87-103
Received Date : 2026-07-10
Revised Date : 2026-08-16
Accepted Date : 2026-08-18
DOI :https://doi.org/10.22680/kasa2026.18.3.087

Journal of Auto-vehicle Safety Association ISSN:2005-9396(Print) 자동차안전학회지

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