Remote Assistance Reservation for Vehicle Operator Priority Scheduling
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Solution Overview
Problem
Existing remote assistance systems for vehicles often result in unnecessary operator preparation and delayed assistance start times due to incorrect timing of assistance needs, leading to wasted operator time and potential delays in responding to new requests.
Innovation Solution
A remote assistance device that predicts assistance provision probability and priority based on travel routes and location information, allowing for reservations to be made for operator assistance, and prioritizes high-priority requests while avoiding low-priority task assignments during existing reservations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If operator preparation is made based on predicted assistance needs, then assistance can be provided at appropriate timings, but unnecessary operator preparation occurs leading to wasted operator time
Solution Approach 1:
The system performs preliminary actions by predicting assistance needs in advance based on travel routes and location information, allowing operators to prepare beforehand. However, it applies preliminary action selectively by using prediction algorithms to identify only those cases where assistance is actually needed, avoiding unnecessary preparation and operator time waste.
Solution Approach 2:
The system uses feedback mechanisms by continuously monitoring travel routes, location information, and assistance outcomes to refine its predictions. This feedback loop ensures that operator preparation is triggered only when assistance is genuinely needed, reducing both assistance start delays and unnecessary operator time consumption.
2Reliability
If reservations are made for high-priority assistance, then timely assistance can be ensured, but low-priority requests may be delayed
Solution Approach 1:
The system applies local quality by differentiating assistance priorities and applying different reservation strategies to different priority levels. High-priority requests receive guaranteed reservation slots to ensure timely assistance, while low-priority requests are handled with flexible scheduling, optimizing resource allocation for each category.
Solution Approach 2:
The system segments assistance requests into different priority categories and manages reservations separately for each segment. This segmentation allows the system to ensure reliable timing for high-priority assistance while preventing indefinite delays of low-priority requests through separate queue management.
3Productivity
If operators are assigned tasks continuously, then operator productivity increases, but assistance quality may deteriorate due to rushed operations
Solution Approach 1:
The system performs preliminary actions by preparing assistance tasks in advance based on predictions, allowing operators to review and plan before execution. This preliminary preparation maintains high productivity by keeping operators continuously engaged while ensuring quality through advance task familiarization and proper sequencing.
Data Source
AI summary
A remote assistance device includes a prediction unit that predicts an assistance provision probability that assistance for a vehicle will be necessary and a priority of the necessary assistance, which are associated with assistance contents of point information, based on a travel route including assistance points and the location information on the assistance points, and a reservation unit that determines whether a reservation for assistance by an operator is necessary based on the assistance provision probability and the priority, and sets, if the reservation is necessary, a reservation for assistance for not assigning an assistance task to the operator even when a low-priority assistance request is newly made while the reservation is held.