Remote Pilot Connectivity Mapping for Stable Vehicle Teleoperation
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Solution Overview
Problem
Teleoperation of vehicles is hindered by variable wireless connectivity issues, including low data throughput and poor data quality between cell towers and vehicles, which disrupts remote driving operations.
Innovation Solution
A system utilizing a connectivity map dynamically updated by network nodes and neighboring vehicles to identify optimal routes maintaining data throughput and quality thresholds, enabling stable remote control through real-time adjustments and historical data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If vehicles use wireless networks for remote driving, then teleoperation capability is enabled, but data throughput and quality become variable and unreliable
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimal routes based on historical connectivity data before the vehicle needs to travel. The computer analyzes past performance data of network nodes and creates a connectivity map that predicts future connectivity conditions, allowing the system to plan routes that are likely to maintain reliable communication without waiting for real-time conditions to improve.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual data throughput and quality during vehicle operation and using this real-time information to update the connectivity map. This feedback loop allows the system to learn from actual performance and refine future route recommendations, gradually improving reliability as the system accumulates more operational data.
2Productivity
If the system dynamically updates connectivity maps with real-time data, then route optimization improves, but system complexity increases
Solution Approach 1:
The system performs self-service by having neighboring vehicles automatically report their measured data throughputs to the computer without requiring manual intervention or complex centralized control. Vehicles autonomously collect connectivity information, process it locally, and share it with the network, distributing the computational workload and reducing the complexity burden on any single system component.
Solution Approach 2:
The system segments the connectivity map into discrete network node entries, each with its own historical and current performance data. This segmentation allows the complex task of route optimization to be broken down into manageable comparisons of individual nodes and segments, making the overall system more tractable and easier to implement while maintaining high optimization efficiency.
3Reliability
If the system requires high data throughput thresholds for remote control, then teleoperation quality improves, but available routes decrease
Solution Approach 1:
The system applies dynamics by adjusting route selection criteria based on current and historical connectivity conditions rather than using fixed thresholds. The computer dynamically evaluates which network nodes and segments have demonstrated reliable performance in similar conditions and adapts route recommendations accordingly, allowing the system to maintain teleoperation quality while maximizing route availability in varying network environments.
Solution Approach 2:
The system changes parameters by using multiple dimensions of performance data (historical average throughput, current measured throughput, variance, time of day, weather conditions) rather than relying on a single fixed threshold. This multi-parameter approach allows the system to identify routes that may have lower average throughput but consistently meet operational requirements under specific conditions, thereby increasing route availability while maintaining quality.
Data Source
AI summary
A system includes network nodes, roadways, vehicles, a computer, and a teledriver facility. The network nodes are distributed along the roadways. Multiple neighboring vehicles reside in segments of the roadways. The vehicle is operational to be driven along the roadways under control of the teledriver facility. The computer is operational to access and dynamically update a connectivity map. The connectivity map identifies multiple data throughputs available between the network nodes and the neighboring vehicles. The computer is further operational to present a route to the teledriver facility to maneuver the vehicle. The route maintains communication between the vehicle and the network nodes with a data connection above a data quality threshold and a data rate threshold. A receiver is disposed in the vehicle to receive driving instructions from the teledriver facility. A drive system is disposed in the vehicle to pilot the vehicle in response to the driving instructions.