Cabin Preference-Based Autonomous Driving for Passenger Comfort
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Solution Overview
Problem
Autonomous driving systems often create uncomfortable driving experiences for passengers, leading to potential reluctance in purchasing autonomous vehicles and sub-optimal driving patterns being developed by vendors.
Innovation Solution
A method and system that generate comfort-based autonomous driving patterns by analyzing driving event metadata, evaluating impact parameters, and determining allowable comfort levels to adjust driving patterns in real-time, using environmental and physical data from sensors, and incorporating feedback from passengers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If autonomous driving systems apply standard driving patterns, then operational efficiency is maintained, but passenger comfort deteriorates
Solution Approach 1:
The system dynamically adjusts driving patterns based on real-time identification of occupants and their preferences. The autonomous driving system transitions from static, pre-programmed driving patterns to dynamic, adaptive patterns that change according to detected passenger characteristics and stated comfort preferences, resolving the contradiction between maintaining operational efficiency and improving passenger comfort.
Solution Approach 2:
The system changes operational parameters of the driving pattern (such as acceleration rates, steering smoothness, braking gentleness) based on identified passenger preferences. By modifying these driving parameters in real-time according to passenger comfort requirements, the system maintains operational efficiency while significantly improving ease of operation and passenger comfort.
2Adaptability or versatility
If autonomous driving systems use generic driving patterns, then system complexity is reduced, but adaptability to individual passengers deteriorates
Solution Approach 1:
The system implements feedback mechanisms where passenger preferences are collected, processed, and used to adjust subsequent driving patterns. The identification system continuously monitors passenger presence and preferences, feeds this information back to the control system, which then adapts driving behavior accordingly. This feedback loop enables high adaptability to individual passengers without requiring overly complex system architecture.
Solution Approach 2:
The system enables passengers to self-define their comfort preferences through input interfaces, and the system automatically applies these preferences to adjust driving patterns. This self-service approach allows the system to adapt to individual passengers using relatively simple logic - the passenger provides preferences and the system autonomously configures appropriate driving parameters, avoiding the need for complex manual configuration or highly sophisticated automated analysis.
Data Source
AI summary
A method that may include receiving driving information and environmental metadata indicative of information sensed by the vehicle; detecting multiple driving events encountered during the driving over the path; determining driving events; for each driving event, determining a comfort based autonomous driving pattern information; for each driving event, determining an driving event identifier; and storing in at least one data structure a driving event identifier for each one of the multiple types of driving events, and a comfort based autonomous driving pattern information.