Autonomous Ridesharing Vehicle Assignment for User and Robot Trips
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Solution Overview
Problem
Current autonomous vehicle systems lack efficient methods to manage and optimize the sharing of vehicles between users and autonomous robots, leading to suboptimal resource utilization and increased costs.
Innovation Solution
A computer-implemented method and system that determines service configurations and assignments for autonomous vehicles to transport users and robots concurrently, optimizing routes and resource allocation to reduce travel time, increase cabin space, and lower service costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles operate independently without sharing, then each vehicle can provide dedicated service to users, but resource utilization decreases and service costs increase
Solution Approach 1:
The patent merges multiple service requests into a single autonomous vehicle trip by combining user transportation needs with autonomous robot delivery needs. The system identifies overlapping routes and consolidates them, allowing one vehicle to simultaneously transport a user and deliver autonomous robots to their destinations, thereby improving resource utilization while maintaining service efficiency
Solution Approach 2:
The autonomous vehicle is designed to perform multiple functions: transporting human users, carrying autonomous robots, and providing delivery services. This multi-functionality allows the vehicle to adapt to different service configurations dynamically, optimizing resource use by selecting the most efficient combination of services for each trip
2Speed
If autonomous vehicles optimize for fastest delivery, then delivery speed improves, but traffic congestion increases and service costs rise
Solution Approach 1:
By combining multiple delivery tasks and user transportation into shared routes, the system reduces the total number of vehicles on the road. This consolidation maintains delivery speed for each individual task while reducing overall traffic congestion through more efficient fleet utilization
Solution Approach 2:
The system dynamically adjusts service configurations based on real-time conditions, selecting between different route options and service combinations. This allows optimization of delivery speed when conditions permit while reducing congestion during peak periods through coordinated routing and timing
Data Source
AI summary
Systems and methods for providing an autonomous vehicle service are provided. A method can include obtaining data indicative of a service associated with a user, and obtaining data indicative of a transportation of an autonomous robot. The method can include determining one or more service configurations for the service. The method can include obtaining data indicative of a selected service configuration from among the one or more service configurations, and determining a service assignment for an autonomous vehicle based at least in part on the selected service configuration. The service assignment can indicate that the autonomous vehicle is to transport the user from the service-start location to the service-end location. The method can include communicating data indicative of the service assignment to the autonomous vehicle to perform the service.