Remote Driving Fleet Allocation for Dynamic Teleoperator Coupling
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Solution Overview
Problem
Existing technologies for managing fleets of vehicles and fleets of teleoperators are inefficient and unreliable, particularly in the context of existing technologies, as they fail to efficiently and reliably address the technical problem of existing technologies, as they fail to efficiently and reliably solve the technical problem of existing technologies, as they fail to efficiently and reliably solve the technical problem of existing technologies, as they fail to effectively and effectively and effectively address the technical solution of existing technologies, as they fail to efficiently and reliably manage fleets of vehicles and teleoperators in remote driving systems.
Innovation Solution
The implementation of a fleet management system that coordinates and instructs multiple vehicles and teleoperators via a wireless communication network, allowing for dynamic remote coupling and uncoupling, enabling safe, efficient, and reliable performance of various tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional one-to-one driver-vehicle relationships are used, then operational simplicity is maintained, but fleet management efficiency and productivity are reduced
Solution Approach 1:
The fleet management system enables one teleoperator to control multiple vehicles sequentially, and one vehicle to be controlled by different teleoperators at different times. This multi-functional capability allows dynamic allocation of teleoperators and vehicles based on task requirements, location, and availability, thereby improving fleet management efficiency without requiring a fixed one-to-one pairing
Solution Approach 2:
The system dynamically couples and uncouples teleoperators with vehicles based on real-time conditions such as task requirements, vehicle location, teleoperator availability, and traffic patterns. This dynamic assignment mechanism allows the fleet to adapt to changing conditions optimally, maximizing productivity while the centralized system manages the coordination complexity
2Reliability
If teleoperators are physically present in vehicles, then direct control is achieved, but safety and efficiency of remote operations are reduced
Solution Approach 1:
The fleet management system acts as an intermediary that coordinates between teleoperators and vehicles, matching them based on multiple factors including task requirements, vehicle location, teleoperator availability, and traffic patterns. This intermediary coordination enables safe and efficient remote operations by ensuring appropriate pairings without requiring physical presence
Solution Approach 2:
The system continuously monitors vehicle location, teleoperator availability, task status, and traffic conditions to dynamically adjust assignments. This feedback mechanism ensures that remote operations are safely coordinated by providing real-time information about system state and making optimal matching decisions
3Productivity
If fixed teleoperator-vehicle assignments are used, then operational simplicity is maintained, but task completion time and productivity are increased
Solution Approach 1:
The fleet management system pre-coordinates teleoperator-vehicle assignments based on predicted task requirements, vehicle locations, and teleoperator availability. By performing assignments in advance based on current system state, the system optimizes task completion efficiency while managing coordination complexity through proactive rather than reactive assignments
Data Source
AI summary
Systems and methods for fleet management of remote driving systems may include a plurality of vehicles and a plurality of teleoperators. A fleet management system may receive a plurality of tasks, and may generate or optimize assignment or allocation of the plurality of tasks to various combinations of the vehicles and teleoperators. Because the teleoperators are decoupled from the vehicles, and because the teleoperators may be dynamically coupled to vehicles via network connections to remotely operate vehicles, performance of the plurality of tasks may be optimized to improve cost, time, and efficiency associated with fleet management of remote driving systems.