Modeling Human Steering Behavior in Teleoperation of Unmanned Ground Vehicles With Varying Speed

Abstract

Objective This paper extends a prior human operator model to capture human steering performance in the teleoperation of unmanned ground vehicles (UGVs) in path-following scenarios with varying speed. Background A prior study presented a human operator model to predict human steering performance in the teleoperation of a passenger-sized UGV at constant speeds. To enable applications to varying speed scenarios, the model needs to be extended to incorporate speed control and be able to predict human performance under the effect of accelerations/decelerations and various time delays induced by the teleoperation setting. A strategy is also needed to parameterize the model without human subject data for a truly predictive capability. Method This paper adopts the ACT-R cognitive architecture and two-point steering model used in the previous work, and extends the model by incorporating a far-point speed control model to allow for varying speed. A parameterization strategy is proposed to find a robust set of parameters for each time delay to maximize steering performance. Human subject experiments are conducted to validate the model. Results Results show that the parameterized model can predict both the trend of average lane keeping error and its lowest value for human subjects under different time delays. Conclusions The proposed model successfully extends the prior computational model to predict human steering behavior in a teleoperated UGV with varying speed. Application This computational model can be used to substitute for human operators in the process of development and testing of teleoperated UGV technologies and allows fully simulation-based development and studies.

Modeling Human Steering Behavior in Haptic Shared Control of Autonomy-Enabled Unmanned Ground Vehicles

“…For teleoperation scenarios, there have been efforts focusing on both small robots (Chen et al, 2007;Ritter et al, 2006Ritter et al, , 2007Vozar, 2013;Vozar et al, 2018) and passenger-sized unmanned ground vehicles (UGVs) (Mirinejad et al, 2018;Li et al, 2020). Such driver models are useful in reducing the time and monetary cost in developing various driving technologies and helping researchers with better understanding the behaviors of the drivers.…”

“…Similar to the control parameters in the human steering models of Mirinejad et al (2018) and Li et al (2020) capturing different driving styles, the control parameters in equation ( 2) are interpreted as describing different reaction styles from the human operator to the autonomy torque feedback from the steering wheel. As shown by Mirinejad et al (2018) and Li et al (2020), the control parameters are scenario dependent and thus a strategy is needed to parameterize the model for specific tracks and situations.…”

“…Because the ability of the human operator affects the performance in the haptic shared control as well, while searching for the set of parameters that gives the best performance, the human steering model is also parameterized to have the best performance (i.e., minimum ALKE) when driving alone. The parameterization strategy for the human steering model is adopted from Li et al (2020), where for each far point control gain k f = 50: À1 : 1, an exhaustive search is performed for time headway thw = 0.5 : 0.1: 2. If a set of parameters can be found that does not result in failure (i.e., tire lift-off), the search terminates and the found set of parameters is used as the best human steering model when driving alone.…”

“…After the exhaustive search is completed, if no viable solution is found, the algorithm moves on to the next k f value in the queue, and another exhaustive search is performed. As shown by Li et al (2020), the near point control parameters k n and k I have negligible impact on the lane keeping performance, as long as they are not set to be too big or too small and affect negatively the stability of the vehicle. Therefore, k n and k I are set manually and are 0.35 and 0.25, respectively.…”

“…Modeling of Human Steering Behavior in Haptic Shared Control ScenariosThe human steering model consists of two components. The first component is a two-point steering model in the cognitive framework ACT-R first introduced bySalvucci (2006) and adapted to the teleoperation setting byMirinejad et al (2018) andLi et al (2020). The second component is a torque conversion module, which converts the steering angle command computed by the two-point steering model into the steering torque command.…”