Autonomous Vehicle G-G Plot Control for Passenger Comfort Adaptation
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Solution Overview
Problem
Current autonomous driving systems lack customization and adaptability to individual user preferences, providing a generic driving experience that may not meet the diverse requirements of passengers, leading to discomfort and inefficiency.
Innovation Solution
A system that uses a g-g plot to represent passenger comfort levels through longitudinal and lateral acceleration parameters, allowing for adaptive vehicle control by identifying dominant factors and updating control parameters based on passenger feedback to maintain preferred dynamics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous driving systems use a uniform risk-averse driving style to ensure safety, then safety is improved, but passenger comfort and customization are worsened
Solution Approach 1:
The system dynamically adjusts driving parameters by maintaining a g-g plot that can be modified in real-time based on passenger feedback. The controller continuously updates the g-g plot parameters (maximum forward acceleration, maximum backward acceleration, maximum lateral acceleration, and shape parameter) to adapt to individual passenger preferences while maintaining safety constraints.
Solution Approach 2:
The system changes physical parameters of vehicle operation by modifying acceleration and deceleration profiles. The g-g plot parameters are adjusted to change the driving style - for example, increasing maximum forward acceleration for passengers who prefer faster trips, or adjusting the shape parameter to change the relationship between longitudinal and lateral accelerations.
2Reliability
If autonomous driving systems follow strict traffic laws and risk-averse behavior, then reliability is improved, but passenger comfort and efficiency are worsened
Solution Approach 1:
The system modifies operational parameters within legal constraints by adjusting the g-g plot. This allows the vehicle to operate more aggressively or conservatively based on passenger preference while remaining within traffic laws. For example, the system can increase acceleration rates or reduce stopping distances up to the limits defined by the modified g-g plot, improving comfort and efficiency without violating rules.
3Adaptability or versatility
If the system collects detailed passenger feedback to customize driving experience, then adaptability is improved, but system complexity and data processing requirements are worsened
Solution Approach 1:
The system implements a feedback mechanism where passengers rate their comfort level after trips or during autonomous operation. The controller uses this feedback to identify which g-g plot parameter should be adjusted and modifies that specific parameter. This structured feedback approach simplifies the processing complexity compared to analyzing continuous detailed data streams.
Solution Approach 2:
The system focuses on changing a limited set of four key parameters (maximum forward acceleration, maximum backward acceleration, maximum lateral acceleration, and shape parameter) rather than adjusting all possible driving parameters. This parameter reduction simplifies the adaptation process while still providing comprehensive customization capability.
4Device complexity
If the system uses a generic driving style for all passengers, then device complexity is reduced, but passenger satisfaction and comfort are worsened
Solution Approach 1:
The g-g plot serves as a universal framework that can represent different driving styles and passenger preferences through a single standardized structure. By maintaining this universal representation and simply modifying its four parameters, the system can accommodate diverse passenger needs without requiring completely different control algorithms for each passenger type.
Data Source
Figure 1A
Figure 1B
Figure 2A
AI summary
A system for controlling an autonomous vehicle includes a memory configured to store parameters of a g-g plot defining admissible space of values of longitudinal and lateral accelerations. The g-g plot parameters define a mapping between user driving preferences and constrained control of the autonomous vehicle. The g-g plot parameters include a maximum forward acceleration, a maximum backward acceleration, a maximum lateral acceleration and a shape parameter defining profile of curves connecting maximum values of forward, backward, and lateral accelerations. The system accepts a comfort level as a feedback from a passenger of the vehicle, determines a dominant parameter corresponding to the feedback, updates the dominant parameter of the g-g plot based on the comfort level indicated in the feedback, and controls the vehicle to maintain dynamics of the vehicle within the admissible space defined by the parameters of the updated g-g plot.