Autonomous Vehicle Trip Routines for Repeated Route Recognition
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Solution Overview
Problem
Existing autonomous vehicle transportation services lack the ability to efficiently recognize, save, and utilize routine trips, particularly those involving intermediate destinations, leading to a less user-friendly experience and reduced convenience.
Innovation Solution
A method and system that allows users to establish and save routine trips by comparing pickup and destination locations to their trip history, providing notifications to suggest routines, and enabling users to confirm and store these routines for later use, which can be displayed on both client computing devices and autonomous vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system provides detailed trip arrangement options and recommendations, then user convenience and experience are improved, but system complexity increases
Solution Approach 1:
The system performs preliminary analysis of trip history data to identify routine patterns before the user requests a trip. By pre-processing the data and having routine recommendations ready in advance, the system reduces the complexity of real-time decision-making while providing convenient, personalized trip suggestions to users.
Solution Approach 2:
The system automatically analyzes user trip patterns and generates routine recommendations without requiring manual user input or complex interactions. The autonomous vehicle system self-services by autonomously identifying routines from historical data and presenting them to users, simplifying the user interface while maintaining sophisticated backend processing.
2Measurement precision
If the system analyzes and stores detailed trip history data, then routine recognition accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential elements needed for routine recognition from the complete trip history data, such as pickup locations, destination locations, and timing patterns. By selectively extracting relevant information rather than processing all raw data, the system achieves accurate routine identification while reducing computational burden and data storage requirements.
Solution Approach 2:
The system performs preliminary filtering and organization of trip history data as it is collected, structuring the information in advance to facilitate efficient routine pattern recognition. This pre-processing step reduces the complexity of subsequent analysis while maintaining the accuracy needed to identify meaningful trip routines.
Data Source
AI summary
Aspects of the disclosure relate to arranging trips for an autonomous vehicle transportation service. In one instance, a request for a first trip from a user is received. The trip may include a pickup location and a destination location. Whether the user has previously completed the first trip may be determined by comparing the pickup location and the destination location to a trip history for the user. Based on the determination, a notification suggesting that the user establish a routine may be provided for display to the user. Confirmation that the user wants to establish a routine based on the pickup location and the destination location may be received. The routine may be stored in memory for later use.