Tire Sensor System for Autonomous Fleet Management
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Solution Overview
Problem
Existing tire sensor systems are ineffective for real-time remote monitoring and management of autonomous vehicle fleets, as they require human intervention to respond to tire parameter alerts, which is not feasible in autonomous vehicles.
Innovation Solution
A tire sensor system that affixes sensors to autonomous vehicle tires to measure parameters like pressure, temperature, and wear, transmitting data wirelessly to a central server for real-time analysis and decision-making, enabling autonomous adjustments to vehicle operations, such as route changes and maintenance scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tire sensors are used in autonomous vehicles, then tire parameter monitoring capability is improved, but human intervention requirement increases system complexity
Solution Approach 1:
The system enables autonomous vehicles to self-monitor tire parameters through integrated sensors and automatically execute decisions based on pre-established algorithms, eliminating the need for human drivers to respond to tire alerts. The vehicle performs self-diagnosis and self-adjustment regarding tire conditions.
Solution Approach 2:
The system continuously collects tire parameter data from sensors, transmits it to remote servers for analysis, and implements feedback loops where algorithms automatically adjust vehicle operations based on tire condition feedback. This closed-loop feedback system replaces human decision-making with automated control.
2Productivity
If real-time tire monitoring is implemented, then vehicle performance optimization is improved, but data transmission and processing requirements increase system complexity
Solution Approach 1:
The system introduces remote servers as intermediaries between the vehicle's sensors and the decision-making algorithms. Sensors on the vehicle transmit tire parameter data to external servers, which then process the information and generate control commands, distributing the computational burden and reducing on-vehicle system complexity.
Solution Approach 2:
The system moves data processing from the traditional on-vehicle dimension to a remote cloud-based dimension. By transmitting data off-vehicle for processing and receiving commands back, the system leverages external computational resources, effectively adding a spatial dimension to the data processing architecture.
3Duration of action of moving object
If autonomous vehicles operate without human drivers, then operational continuity is improved, but response to tire alerts becomes problematic
Solution Approach 1:
The system pre-establishes algorithms and decision-making protocols before the vehicle operates autonomously. These pre-programmed instructions enable the vehicle to automatically respond to tire parameter alerts without human intervention, maintaining operational continuity by having responses ready in advance.
Solution Approach 2:
The autonomous vehicle performs self-monitoring and self-response regarding tire conditions through integrated sensors and automated decision algorithms. When tire parameters indicate issues, the system automatically executes predetermined actions such as adjusting vehicle operations or scheduling maintenance, eliminating the need for human drivers to respond to alerts.
Data Source
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AI summary
A system (50) for sensing tire parameters in the remote monitoring and management of a fleet of autonomous vehicles (24) is provided. The system (50) includes at least one autonomous vehicle (24) that is supported by at least one tire (10). At least one sensor (22) is affixed to the tire (10) for sensing tire parameters. Means are provided for communicating data generated by the sensor (22) to a control system on the vehicle (24), and a mobile network (34) receives the sensor data from the vehicle control system. A fleet management server (38) receives the sensor data from the mobile network (34), and means are provided to generate commands for the autonomous vehicle (24) in real time based upon the data generated by the sensor (22). A method for sensing tire parameters in the remote monitoring and management of a fleet of autonomous vehicles (24) is also provided.