Self-Driving Vehicle Feature Presentation Using Autonomous Demonstrations
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Solution Overview
Problem
Self-driving vehicles (SDVs) face challenges in efficiently and automatically presenting their features to potential consumers, as existing methods lack the ability to analyze consumer preferences and contexts in real-time, leading to ineffective demonstrations of handling capabilities and features.
Innovation Solution
A computer-implemented system that determines SDV features of interest based on consumer observations and contexts, generating instructions for the SDV to perform tasks that highlight these features, such as navigating to a consumer's location or demonstrating handling capabilities, using a cloud computing environment for data processing and task management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If self-driving vehicles use traditional manual presentation methods, then human intervention is required to showcase features, but this reduces automation and efficiency
Solution Approach 1:
The self-driving vehicle autonomously identifies consumer interests, selects relevant features, and presents them through self-driven demonstrations without human intervention. The vehicle serves itself by automatically analyzing consumer data, determining appropriate features, executing demonstration tasks, and adapting presentations based on real-time consumer reactions.
2Productivity
If self-driving vehicles present all features to all consumers, then comprehensive information is provided, but this wastes time and resources on irrelevant features
Solution Approach 1:
The system customizes the feature presentation by identifying specific consumer interests and selecting only the relevant features to demonstrate. Instead of uniformly presenting all features to all consumers, the vehicle tailors the presentation content to match individual consumer preferences, thereby improving efficiency while maintaining information relevance.
Solution Approach 2:
The system dynamically adjusts the feature presentation parameters based on consumer data analysis. By changing which features are presented, how they are demonstrated, and the sequence of presentation based on consumer interests and reactions, the system optimizes both efficiency and information tailoring.
3Ease of operation
If self-driving vehicles perform complex demonstration tasks, then feature capabilities are effectively showcased, but this increases system complexity
Solution Approach 1:
The self-driving vehicle leverages its existing autonomous driving capabilities and sensor systems to perform feature demonstrations. The same systems used for navigation, obstacle detection, and path planning are utilized to execute demonstration tasks, thereby showcasing features without requiring separate dedicated demonstration hardware or systems.
Solution Approach 2:
The system uses the autonomous driving control system as an intermediary to translate consumer interest data into actionable demonstration tasks. The control system mediates between the consumer preference analysis and the physical vehicle actions, coordinating steering, acceleration, and other functions to execute demonstrations while maintaining system manageability.
Data Source
AI summary
Techniques for facilitating the autonomous presentation of a self-driving vehicle are provided. In one example, a method can include a system operatively coupled to a processor, where the system: determines a feature of a self-driving vehicle based on information regarding an entity in a pending transaction; determines a task to be performed by the self-driving vehicle based on the feature; and generates an instruction for the self-driving vehicle to perform the task.