Design of Haptic Protection with an Adaptive Level of Authority Based on Risk Indicators under Hands-on Partial Driving Automation

Saito, Yuichi; Muslim, Hussam; Itoh, Makoto · 2021 · Crossref

DOI: 10.1109/smc52423.2021.9658933

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Summary

This paper addresses the challenge of designing haptic protection systems for hands-on partial driving automation, specifically focusing on lane change scenarios involving blind spot risks. The authors aim to mitigate "automation surprise" and driver distrust by implementing a shared control system that communicates hazardous situations through steering wheel stiffness rather than abrupt braking interventions. The core research question investigates how to share control authority at tactical (decision-making) and operational (continuous control) levels using an adaptive level of haptic authority (LoHA) based on risk indicators. The study proposes a haptic protection system that utilizes artificial stiffness around the driver’s desired steering angle to warn against inappropriate actions, distinct from haptic guidance systems that steer toward a normative path. The design integrates two risk indicators: Time-to-Contact (TTC) and Time Headway (THW). A Risk Perception (RP) metric is calculated as a weighted sum of the inverses of THW and TTC ($RP = A/THW + B/TTC$). This RP value dynamically adjusts the additional stiffness coefficient ($K_{added}$), which ranges from 0 to 3, thereby modulating the resisting torque applied to the steering wheel. The system combines this protection torque with standard lane centering guidance torque. To evaluate the design, the authors conducted a simulation study using MATLAB with a general two-wheel vehicle model and a look-ahead driver model. The simulation tested three conditions: (a) haptic guidance only, (b) combined haptic guidance and protection, and (c) haptic protection only. Scenarios varied based on the approaching vehicle's THW, ranging from 3.15 to 0.45 seconds, while TTC was set to infinity for steady-state analysis. The evaluation focused on lateral position, steering angle, and the time elapsed until lane deviation. The results demonstrated that the combined system (guidance plus protection) effectively resisted inappropriate lane change attempts more powerfully than guidance alone. The adaptive stiffness feedback increased the perceived effort required to steer into the blind spot, causing the driver model to reduce the maximum steering angle and maintain lane position. The study concluded that this shared control approach allows drivers to recognize the inappropriateness of their actions at both tactical and operational levels. By manipulating steering stiffness based on covert risk indicators, the system provides continuous haptic information about hazardous environments, enhancing safety without removing the driver from the control loop or causing sudden automation surprises.

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Topics

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• hands on hands off engagement
• automation
• haptic feedback
• automation surprise
• manual
• takeover transitions

Information type

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• Applied Guidance: design guidelines
• Theoretical Contribution: conceptual framework, computational model