Modular Autonomous Vehicle Task Matching With Capability Verification
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Solution Overview
Problem
The gig economy for humans has limitations, and the expanding capabilities of autonomous vehicles pose opportunities for them to perform tasks, but variability in vehicle capabilities means not all can complete tasks, and some require human input, necessitating a system to verify vehicle capabilities and enable combined human-autonomous task completion.
Innovation Solution
A system that allows autonomous vehicles to be algorithmically interrogated to ensure task capability, combining with human assistance, and offering flexible fares based on arrival time, using a platform to match vehicle capabilities with jobs and optimize revenue through a gig economy framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicles are designed with modular capabilities to perform multiple functions, then vehicle versatility is improved, but variability in capabilities between vehicles increases making task verification more complex
Solution Approach 1:
The system implements algorithmic interrogation that provides feedback loops between task requirements and vehicle capabilities. The platform automatically verifies whether vehicle sensors, cameras, and equipment meet task specifications through systematic questioning and validation, resolving the complexity of matching modular vehicle capabilities with diverse gig economy tasks.
Solution Approach 2:
The verification platform serves multiple functions: it assesses vehicle capabilities, matches vehicles with appropriate tasks, validates equipment presence, and coordinates human assistance needs. This universal system handles the complexity of varied vehicle configurations through a single multi-functional verification mechanism.
2Reliability
If the system algorithmically interrogates autonomous vehicles to verify task capability, then task completion reliability is improved, but system complexity increases
Solution Approach 1:
The algorithmic interrogation system is segmented into modular components that assess different aspects of vehicle capability independently: sensor verification, camera functionality, equipment presence, and human assistance requirements. This segmentation makes the complex verification process manageable and systematic while maintaining high reliability.
3Measurement precision
If the platform matches vehicle capabilities with specific jobs through technical assessment, then job fulfillment accuracy is improved, but matching process complexity increases
Solution Approach 1:
The system enables autonomous vehicles to self-assess and self-report their capabilities through algorithmic interrogation. Vehicles automatically provide information about their sensors, cameras, and equipment, allowing the platform to perform accurate capability-job matching without complex manual assessment procedures.
4Adaptability or versatility
If human assistance is integrated into the gig-based system for task completion, then task capability flexibility is improved, but coordination complexity increases
Solution Approach 1:
The platform acts as an intermediary that coordinates between autonomous vehicles and human assistants. It identifies tasks requiring human input, matches appropriate human workers with vehicle-based tasks, and manages the integration of human and autonomous capabilities, simplifying the coordination complexity through centralized platform management.
Data Source
AI summary
A method for fulfilling a work task request using a modular autonomous vehicle is provided. The method includes transmitting a work task request specifying a work request to be performed by the modular autonomous vehicle, and identifying equipment required for performing the work task request. Once the work task request is stored at a server, the method further includes identifying information of the equipment required for performing the work task request, and determining whether equipment of the modular autonomous vehicle corresponds to the equipment required for assigning the work task to the modular autonomous vehicle. Method also includes, upon receiving in-cabin sensing data, assigning or denying the work task to the modular autonomous vehicle for performance of the work task.