Autonomous Vehicle Collision Avoidance with Segmented Sensor Zones
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Solution Overview
Problem
In industrial sites where autonomous vehicles and robots coexist, the current collision avoidance systems often lead to unnecessary stops due to excessive sensor detection areas, resulting in delayed task progress and potential collisions between vehicles.
Innovation Solution
A system employing a first sensor for detecting objects in a specific area and a second sensor, like LIDAR, to detect vehicles with reflective indication parts, allowing the processor to control autonomous driving by distinguishing between objects and vehicles, and requesting driving permission from a control server to avoid collisions without unnecessary stops.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the sensor detection area is reduced to prevent unnecessary stops, then task progress efficiency is improved, but collision detection capability deteriorates
Solution Approach 1:
The detection system is segmented into multiple sensors with different detection areas and functions. The first sensor detects objects in a first detection area, while the second sensor detects vehicles in a second detection area. This segmentation allows each sensor to be optimized for its specific detection target, preventing unnecessary stops while maintaining collision detection capability.
Solution Approach 2:
The patent introduces a new dimension of detection by adding a second sensor that operates in a different detection area than the first sensor. This dimensional expansion of the detection system enables simultaneous monitoring of both objects and vehicles without compromising either detection capability.
2Reliability
If the sensor detection area is expanded to detect all obstacles, then collision detection capability is improved, but unnecessary stops increase
Solution Approach 1:
Different parts of the detection system have different detection areas and detection targets. The first sensor is configured with a first detection area optimized for detecting objects, while the second sensor has a second detection area optimized for detecting vehicles. This local quality differentiation ensures that each sensor detects only what it is designed for, preventing unnecessary stops while maintaining comprehensive collision detection.
Solution Approach 2:
The detection system is divided into specialized segments where the first sensor handles object detection and the second sensor handles vehicle detection. This segmentation prevents the first sensor from triggering unnecessary stops due to detecting non-vehicle objects, while the second sensor ensures vehicle collision detection capability is maintained.
3Device complexity
If a single sensor is used for detecting all obstacles, then device complexity is reduced, but detection accuracy deteriorates
Solution Approach 1:
The detection system is segmented into a first sensor for object detection and a second sensor for vehicle detection. This segmentation improves detection accuracy by assigning specific detection tasks to specialized sensors, while the overall system complexity remains manageable through modular architecture and coordinated operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables autonomous vehicles to navigate efficiently without frequent stops, effectively preventing collisions by accurately differentiating between obstacles and other vehicles, thus enhancing task progress and safety in shared industrial spaces.
Implementation Method 1
The second sensor may be a LIDAR sensor that detects the indication part
Implementation Method 2
The indication part may include a reflective material
Data Source
AI summary
A system for avoiding a collision of an autonomous vehicle that drives through a space in which a plurality of zones have been set including a first sensor configured to detect objects disposed in a first detection area, a second sensor configured to detect another vehicle disposed in a second detection area, and a processor configured to control an autonomous driving operation of the autonomous vehicle by distinguishing between an object detected by the first sensor and the another vehicle detected by the second sensor and control an entry of the autonomous vehicle through the autonomous driving operation into any one zone of the plurality of zones in response to a driving signal that is received from a control server.