Driver Takeover Readiness Cues for Autonomous Driving Handover
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The transition of control from an autonomous driving system to a human driver is often abrupt, posing safety risks due to a lack of seamless interaction and reduced situation awareness of the driver, especially after prolonged autonomous driving periods.
Innovation Solution
A method that obtains data on the driver's state and the current autonomous driving segment to tailor requests prompting reactions, increasing situation awareness through physical and mental engagement, with safety procedures if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If control transitions directly from autonomous driving system to human driver without preparation, then the transition process is simple and quick, but the driver's situation awareness is reduced and safety risks increase
Solution Approach 1:
The system performs preliminary actions by providing tailored requests to the driver before control transition occurs. These requests prompt the driver to engage in specific actions (e.g., checking mirrors, adjusting seating position) that prepare the driver for takeover, ensuring situation awareness is restored before actual control transfer.
Solution Approach 2:
The transition process is segmented into multiple phases: monitoring driver state, assessing readiness, providing tailored requests, and finally executing control transfer. This segmentation allows the system to manage complexity by breaking down the transition into manageable steps while maintaining overall safety.
2Reliability
If the driver is monitored continuously to assess readiness for takeover, then the safety and smoothness of control transition is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The monitoring system uses multi-functional sensors that can detect multiple driver states simultaneously (e.g., eye tracking for attention, posture sensors for seating position, biometric sensors for stress levels). This universal approach reduces the need for separate specialized sensors for each monitoring parameter.
Solution Approach 2:
The system continuously monitors driver state and provides real-time feedback through tailored requests. The monitoring process itself generates feedback loops where the system adjusts requests based on driver responses, creating a dynamic assessment of readiness without requiring overly complex hardware.
3Reliability
If tailored requests are provided based on driver state and autonomous driving segment data, then the driver's situation awareness is enhanced, but the data processing and request generation complexity increases
Solution Approach 1:
The system provides locally tailored requests based on the specific driver state and context rather than generic warnings. Each request is customized to the driver's current condition (e.g., if the driver is looking at the phone, the request might be to check the rearview mirror; if the driver is sleepy, the request might involve more engaging actions). This localized approach maximizes effectiveness while managing processing complexity through context-aware filtering.
Data Source
Figure 1~3
AI summary
The invention relates to a method for preparing a human driver (14) to take over control of a vehicle (10) from an autonomous driving system (12). The method comprises obtaining first data (D1) indicative of a state of the human driver (14) and/or second data (D2) indicative of a current autonomous driving segment. Moreover, the method comprises causing a request (R) to be provided to the human driver (14), wherein the request (R) prompts a reaction of the human driver (14) and wherein the request (R) is based on the first data (D1) and/or on the second data (D2). Furthermore, the method comprises providing data indicative of a readiness of the human driver (14) for take-over of the control of the vehicle (10) based on data generated by the human driver (14) in reaction to the request (R). Additionally, a data processing apparatus (22), a computer program (30), a computer-readable storage medium (28), and a vehicle (10) are presented.