Autonomous Driving Transition Control for Driver-Intent Alignment
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Solution Overview
Problem
Autonomous driving systems face challenges in managing transitions between autonomous and manual driving modes, leading to decreased user trust due to frequent enabling and disabling of autonomous functions, and require adjustments based on driver intent and situational awareness.
Innovation Solution
A driving control module that determines future times for initiating and ending autonomous driving, adjusts parameters based on driver input, and reschedules or cancels autonomous driving events based on probability and situational awareness to ensure safe and efficient transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous driving is frequently enabled and disabled, then the system can adapt to driver intent and situational awareness, but user trust decreases
Solution Approach 1:
The system determines a future time for beginning autonomous driving in advance, allowing the system to prepare for mode transitions proactively rather than reactively. This preliminary planning reduces frequent switching by anticipating appropriate moments for autonomous operation based on predicted driver availability and situational factors.
Solution Approach 2:
The system dynamically adjusts the autonomous driving schedule based on real-time driver input and situational awareness. The driving control module monitors driver behavior and can selectively delay or cancel autonomous driving periods, creating a flexible system that adapts to changing conditions while maintaining overall stability and reducing unnecessary transitions.
2Productivity
If the system determines future times for autonomous driving, then transitions between modes can be optimized, but system complexity increases
Solution Approach 1:
The driving control module performs multiple functions: it determines future times for autonomous driving, monitors driver input, assesses situational awareness, and adjusts driving parameters. By consolidating these diverse functions into a single control module, the system achieves transition optimization without proportionally increasing overall system complexity.
Solution Approach 2:
The system adjusts driving parameters based on driver input during autonomous driving, such as modifying lane positioning or turning behavior. This parameter adjustment capability allows the system to optimize transitions and adapt to driver intent without requiring complex architectural changes,而是 by dynamically modifying operational parameters.
3Reliability
If short instances of autonomous driving are minimized, then user trust is enhanced, but autonomous driving usage is reduced
Solution Approach 1:
By determining future times for autonomous driving in advance and assessing whether these periods will be sufficiently long, the system can proactively cancel short instances before they occur. This prevents trust-decreasing frequent short transitions while still maximizing meaningful autonomous driving usage by focusing on longer, more beneficial periods.
Solution Approach 2:
The system dynamically evaluates the duration and appropriateness of each planned autonomous driving period, selectively delaying or canceling those that would be too short to provide value. This dynamic filtering ensures that autonomous driving is used maximally for meaningful durations while eliminating counterproductive short instances that would harm user trust.
Data Source
AI summary
An autonomous driving system of a vehicle includes: an autonomous module configured to, during autonomous driving, control at least one of: steering of the vehicle; braking of the vehicle; and acceleration and deceleration of the vehicle; and a driving control module configured to: enable and disable autonomous driving; determine a future time for beginning a period of autonomous driving; and at least one of: selectively delay the beginning of autonomous driving to after the future time; and cancel the period of autonomous driving.