Working Vehicle Curve Radius Control and GNSS Slow-Zone Speeding
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Solution Overview
Problem
Autonomous and remotely controlled vehicles lack the ability to autonomously identify and adapt to terrain features and conditions that require speed reduction to avoid damage, such as sharp curves and challenging soil conditions, and often rely on unreliable internet connectivity for navigation, leading to safety and efficiency issues in agricultural and work operations.
Innovation Solution
Implementing systems that use GNSS units and sensors to identify slow zones, determine upcoming curve radii, and adjust speed, along with vehicle-to-vehicle communication for maintaining connectivity and enabling independent switching between autonomous and manual control modes, and integrating edge computing for real-time path planning and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle operates at high speed to achieve greatest efficiency, then productivity is improved, but the vehicle may become stuck or damage the vehicle, towed implement, objects, or the work area itself
Solution Approach 1:
The system performs preliminary identification of slow zones using GNSS 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 identified 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 GNSS, terrain conditions via sensors, and speed parameters. This feedback loop enables the autonomous control system to dynamically adjust speed in real-time based on actual vehicle location relative to identified slow zones, ensuring high speed operation is maintained wherever safe while automatically reducing speed when approaching areas that could cause damage
2Reliability
If a driver manually reduces vehicle speed to avoid damage in slow zones, then safety is improved, but the operational efficiency decreases due to lack of autonomous detection capability
Solution Approach 1:
The autonomous vehicle system performs self-detection of slow zones using onboard GNSS units and sensors to identify terrain features and conditions. The system independently determines its own speed adjustments without requiring external human intervention, enabling continuous autonomous operation that maintains both safety in slow zones and overall operational efficiency
Solution Approach 2:
The patent replaces the mechanical system of human driver perception and manual control with an autonomous electronic control system. The autonomous system uses GNSS coordinate matching, sensor data processing, and automated throttle/steering control to perform functions that would otherwise require a human driver to continuously monitor terrain and manually adjust speed, thereby maintaining safety while eliminating downtime associated with manual intervention
3Productivity
If the vehicle traverses sharp curves at high speed, then productivity is improved, but the vehicle or towed implement may become damaged
Solution Approach 1:
The system pre-identifies sharp curves and other challenging terrain features using GNSS coordinate data and digital terrain models before the vehicle encounters them. The autonomous control system calculates appropriate speed reduction profiles in advance and prepares steering commands, allowing the vehicle to approach curves at optimal speeds and navigate them safely without sudden maneuvers that could cause damage
Solution Approach 2:
The autonomous control system dynamically adjusts vehicle speed and steering in real-time based on the identified curve characteristics and current vehicle state. The system continuously modifies control parameters to optimize performance through each curve, maintaining higher speeds where terrain allows while automatically reducing speed on sharper curves to prevent damage, thereby balancing productivity and safety
4Adaptability or versatility
If cloud-based control algorithms are used for autonomous vehicle operation, then navigation capability is improved, but the system becomes vulnerable to internet connectivity issues and evacuation scenarios
Solution Approach 1:
The system implements local quality by distributing intelligence between cloud-based and onboard processing. Critical safety functions and basic navigation operate autonomously using onboard sensors and pre-loaded terrain data, ensuring reliability during connectivity loss. Enhanced navigation capabilities and complex path planning utilize cloud-based algorithms when available, optimizing performance without creating single points of failure
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.