Autonomous Vehicle Speed Control for Terrain Damage Avoidance
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Solution Overview
Problem
Autonomous and remotely controlled vehicles lack the ability to autonomously identify and adjust speed for terrain features, soil types, and other conditions that require speed reduction to avoid damage, and they also struggle with adapting turn speeds while maintaining path accuracy.
Innovation Solution
The system employs a combination of GPS, cameras, and sensors to identify slow zones and determine the radius of upcoming curves, adjusting vehicle speed accordingly. It also adapts turn speeds based on real-time soil conditions and path error, and allows for independent switching between autonomous and manual modes for steering, throttle, and implement control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle operates at high speed to achieve maximum efficiency, then productivity is improved, but the risk of damage to the vehicle, implement, or work area increases when encountering terrain features or sharp curves
Solution Approach 1:
The system performs preliminary identification of slow zones using GPS coordinates and terrain data before the vehicle reaches them. The autonomous control system pre-calculates speed reduction requirements and prepares control commands in advance, allowing the vehicle to maintain high speed until approaching the slow zone, then smoothly transition to reduced speed to avoid damage while minimizing productivity loss.
Solution Approach 2:
The system continuously monitors vehicle position via GPS, compares current location with stored slow zone coordinates, and dynamically adjusts speed based on real-time feedback. When the vehicle approaches a slow zone boundary, the system receives feedback about the approaching condition and automatically modulates speed to prevent damage, creating a closed-loop control system that balances productivity and safety.
2Reliability
If the vehicle reduces speed to navigate sharp curves safely, then the risk of damage is reduced, but productivity decreases due to slower operation
Solution Approach 1:
The system identifies sharp curves and slow zones in advance using pre-stored GPS coordinate data from field mapping. Before the vehicle reaches these hazardous areas, the autonomous control system pre-calculates the optimal speed reduction profile, allowing the vehicle to maintain maximum speed during safe zones and only reduce speed when necessary, thereby minimizing the impact on overall productivity while ensuring safe navigation.
Solution Approach 2:
The system dynamically adjusts vehicle speed based on real-time position feedback relative to slow zones and curve radii. The speed modulation is not static but continuously adapted as the vehicle approaches, enters, and exits slow zones, optimizing the balance between safety and productivity by reducing speed only when and where necessary rather than maintaining reduced speed throughout the entire operation.
3Productivity
If autonomous vehicles are deployed without human operators, then productivity and operational continuity are improved, but the ability to perceive and respond to changing terrain conditions deteriorates
Solution Approach 1:
The autonomous vehicle system performs self-perception and self-control by using onboard GPS receivers to determine its position, automatically comparing current location with pre-stored slow zone coordinates, and independently modulating speed without human intervention. The system serves itself by integrating navigation, terrain recognition, and control functions into an autonomous loop that maintains productivity and adapts to terrain conditions without requiring human operators.
Solution Approach 2:
The patent replaces the human driver's biological perception and manual control mechanisms with electronic and software-based systems. GPS receivers, microprocessors, and autonomous control algorithms substitute for human visual perception, judgment, and manual throttle/steering control, enabling the vehicle to autonomously identify slow zones and adjust speed based on digital terrain data, thereby maintaining adaptability while ensuring operational continuity.
4Productivity
If the vehicle maintains high speed through areas with varying soil conditions, then productivity is improved, but wheel slippage and damage to crops or work area increase
Solution Approach 1:
The system uses pre-mapped GPS coordinates of slow zones that include areas with challenging soil conditions, steep slopes, or sensitive crops. Before the vehicle reaches these areas, the autonomous control system has already prepared speed reduction commands based on the stored geographic data, allowing the vehicle to maintain high speed in safe zones and automatically reduce speed in advance when approaching vulnerable areas, thereby preventing wheel slippage damage while minimizing productivity loss.
Solution Approach 2:
The autonomous control system continuously receives feedback from GPS position data and compares it with the stored map of slow zones containing sensitive areas. This real-time feedback loop enables the system to detect when the vehicle is approaching areas prone to wheel slippage or crop damage and automatically adjust speed accordingly, creating a dynamic control mechanism that protects the work area while maintaining optimal productivity.
Data Source
AI summary
Various apparatus and procedures for improved operation of a working vehicle are provided. One embodiment provides for identifying areas where the vehicle must decrease speed in order to avoid damage to the vehicle or implement. Another embodiment provides for calculating the radius of an upcoming curve and adjusting vehicle speed as needed to avoid damage to the vehicle, implement, objects, or the work area. Another embodiment provides for adapting turning speed while maintaining acceptable path error. Another embodiment provides a method for directing a vehicle to an evacuation location. Another embodiment provides a method for switching vehicle and implement control from cloud-based control algorithms to in-vehicle control algorithms in the event of an evacuation.