Estimation and Decomposition of Rack Force for Driving on Uneven Roads

The force transmitted from the front tires to the steering rack of a vehicle, called the rack force, plays an important role in the function of electric power steering (EPS) systems. Estimates of rack force can be used by EPS to attenuate road feedback and reduce driver effort. Further, estimates of the components of rack force (arising, for example, due to steering angle and road profile) can be used to separately compensate for each component and thereby enhance steering feel. In this paper, we present three vehicle and tire model-based rack force estimators that utilize sensed steering angle and road profile to estimate total rack force and individual components of rack force. We test and compare the real-time performance of the estimators by performing driving experiments with non-aggressive and aggressive steering maneuvers on roads with low and high frequency profile variations. The results indicate that for aggressive maneuvers the estimators using non-linear tire models produce more accurate rack force estimates. Moreover, only the estimator that incorporates a semi-empirical Rigid Ring tire model is able to capture rack force variation for driving on a road with high frequency profile variation. Finally, we present results from a simulation study to validate the component-wise estimates of rack force.

The Effects of Driver Coupling and Automation Impedance on Emergency Steering Interventions

Automatic emergency steering maneuvers can be used to avoid more obstacles than emergency braking alone. While a steer-by-wire system can decouple the driver who would essentially act as a disturbance during the emergency steering maneuver, the alternative in which the steering wheel remains coupled would enable the driver to cover for automation faults and conform to regulations that require the driver to retain control authority. In this paper we present results from a driving simulator study with 48 participants in which we tested the performance of three emergency steering intervention schemes. We analyzed cases in which the driver was decoupled and the automation given full authority, or the driver was coupled and the automation given a low impedance, or the driver was coupled and the automation given a high impedance. Two types of unexpected automation faults were also simulated. Results showed that a high impedance automation system results in significantly fewer collisions during intended steering interventions but significantly higher collisions during automation faults when compared to a low impedance automation system. Moreover, decoupling the driver in emergency interventions did not seem to significantly increase the time required to hand back control to the driver. When coupled, drivers were able to cover for a faulty automation system and avoid obstacles to a certain degree, though differences by condition were significant for only one type of automation fault.

Impedance Modulation for Negotiating Control Authority in a Haptic Shared Control Paradigm

Communication and cooperation among team members can be enhanced significantly with physical interaction. Successful collaboration requires the integration of the individual partners' intentions into a shared action plan, which may involve a continuous negotiation of intentions and roles. This paper presents an adaptive haptic shared control framework wherein a human driver and an automation system are physically connected through a motorized steering wheel. By the virtue of haptic feedback, the driver and automation system can monitor each other actions, and can still intuitively express their control intentions. The objective of this paper is to develop a systematic model for an automation system that can vary its impedance such that its interaction with a human partner occurs as smoothly as that same interaction would occur between two humans. To this end, we defined a cost function that not only ensures the safety of the collaborative task but also takes account for the assistive behavior of the automation system. We employed a predictive controller based on modified non-negative least square to modulate the automation system impedance such that the cost function is optimized. The results demonstrate the significance of the proposed approach for negotiating the control authority, specifically when human and automation are in a non-cooperative mode. Furthermore, the performance of the adaptive haptic shared control is compared with the traditional haptic shared control paradigm. Finally, future experimental plan, its challenges, and our solution for those challenges are discussed.