Suggesting Remote Vehicle Assistance Actions
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Solution Overview
Problem
Autonomous vehicles may encounter disruptions that require fast resolutions to ensure safe and effective operation without adverse effects on the vehicle, occupants, or surroundings, but existing systems lack efficient methods for rapid scenario resolution.
Innovation Solution
A system that provides remote assistance to autonomous vehicles by suggesting actions based on historical data, allowing operators to quickly choose from statistically validated options, reducing the time required to resolve scenarios and enhancing confidence through data-driven decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles operate independently without remote assistance systems, then vehicle autonomy is maintained, but resolution time for disruptions increases and safety may be compromised
Solution Approach 1:
The patent introduces a remote assistance system as an intermediary between autonomous vehicles and human operators. This mediator provides suggested actions to operators during disruptions, enabling faster resolution while maintaining vehicle autonomy. The system acts as a bridge that enhances safety and reduces resolution time without requiring full manual intervention.
Solution Approach 2:
The patent replaces the traditional mechanical approach of direct human control with an automated suggestion system. Instead of operators directly controlling vehicles or waiting for full manual takeover during disruptions, the system uses automated analysis to generate suggested actions, substituting manual decision-making processes with algorithmic assistance.
2Productivity
If operators handle scenarios without suggested actions, then full decision-making autonomy is maintained, but operator stress increases and resolution efficiency decreases
Solution Approach 1:
The system enables operators to serve themselves by providing automated suggested actions based on historical data and scenario analysis. Operators can quickly review and select from pre-analyzed options rather than conducting full analysis themselves, reducing stress while maintaining decision-making autonomy and improving resolution efficiency.
Solution Approach 2:
The system implements feedback loops where operator selections are fed back into the historical data repository, continuously improving the quality of suggested actions. This feedback mechanism allows the system to learn from actual operator decisions and refine future suggestions, enhancing both efficiency and ease of operation over time.
3Measurement precision
If historical scenario data is not utilized, then system simplicity is maintained, but decision-making accuracy and operator confidence decrease
Solution Approach 1:
The system performs preliminary analysis of historical scenario data in advance, storing processed insights and patterns that can be quickly retrieved during disruptions. By pre-processing and organizing historical data into actionable suggestions, the system improves decision-making accuracy without adding significant complexity during critical resolution moments.
Data Source
AI summary
Provided are methods for data-driven suggested remote vehicle assistance actions, which can include in response to receiving a request from a vehicle requesting assistance to address a scenario involving the vehicle, determining, using data stored in at least one data structure regarding a plurality of previously resolved scenarios involving a plurality of vehicles, a plurality of actions to address the scenario, causing an indication of the plurality of actions to be provided on at least one display remotely located from the vehicle, receiving a user selection of one of the plurality of actions; and causing an instruction to be transmitted to the vehicle based on the selected one of the plurality of actions. Systems and computer program products are also provided.