Dynamic Obstacle Height Threshold for Vehicle Collision Avoidance
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Solution Overview
Problem
Existing vehicle detection systems are prone to incorrectly identifying road features like manhole covers as obstacles, especially on non-highway roads, and lack functionality in vehicles without navigation devices, compromising safety.
Innovation Solution
An object type determination apparatus mounted in vehicles, utilizing a millimeter wave sensor and image sensor to detect objects, estimate their height from the road surface, and assess the likelihood of complex environments, adjusting criteria for collision avoidance based on these factors to enhance safety and prevent unnecessary system activation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed threshold is used to determine obstacles, then the system is simple to operate, but it incorrectly identifies road features as obstacles on non-highway roads
Solution Approach 1:
The determination threshold is made dynamic by adjusting it based on the detected road class (highway vs. non-highway). The system automatically selects different threshold values depending on the environment, transforming a static operation into an adaptive one that maintains reliability across varying road conditions without requiring manual intervention.
Solution Approach 2:
The system changes the threshold parameter based on the detected road class. When a highway is detected, a higher threshold is applied; when a non-highway is detected, a lower threshold is applied. This parameter adaptation resolves the contradiction by maintaining both simplicity in operation and accuracy in obstacle detection across different environments.
2Reliability
If the threshold is raised to prevent misidentification on highways, then false obstacle detection decreases, but legitimate obstacles on non-highways may be missed
Solution Approach 1:
The system applies different threshold criteria to different road types (highway vs. non-highway). By detecting the road class first and then selecting the appropriate threshold, the system ensures high reliability for highway obstacles while maintaining adaptability to non-highway environments with different obstacle characteristics.
Solution Approach 2:
The threshold is dynamically adjusted based on the detected road class, allowing the system to adapt its sensitivity automatically. This dynamic adjustment ensures that the system is reliable on highways while remaining adaptable to the diverse obstacle types found on non-highway roads.
3Reliability
If navigation device is used for road class determination, then obstacle detection accuracy improves, but system complexity increases and becomes unavailable in vehicles without navigation
Solution Approach 1:
The system extracts and uses only the essential information needed for road class determination without requiring the entire navigation device. By isolating the specific functionality needed (road class detection) from the complex navigation system, the patent enables obstacle detection accuracy improvement while reducing the requirement for full navigation hardware availability.
4Measurement precision
If height estimation is performed with high precision, then obstacle identification accuracy improves, but processing time increases
Solution Approach 1:
The system performs height estimation to a sufficient degree to differentiate obstacle types without excessive precision. By applying the determination criteria with appropriate threshold values based on road class, the system achieves adequate measurement precision for safe operation while avoiding unnecessary computational time consumption from overly precise measurements.
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
The system effectively determines whether detected objects require collision avoidance actions, improving vehicle safety by accurately identifying obstacles and preventing false activations in complex environments.
Implementation Method 1
detects an object, such as a pedestrian or the like, present outside of a controlled vehicle (i.e., a vehicle mounting therein the apparatus) with a radar
Implementation Method 2
utilizing a millimeter wave sensor and image sensor to detect objects
Data Source
AI summary
An object type determination apparatus mounted in a vehicle. In the apparatus, a detection unit detects an object present forward of the vehicle. A height estimation unit estimates a height of the object detected by the detection unit from a road surface. A determination unit uses the estimation result of the height estimation unit to determine, according to one of a plurality of predefined criteria, whether or not the object is an object for which a collision avoidance process is performed. A complex environment estimation unit estimates a likelihood that a complex environment is present forward of the vehicle. A criterion selection unit selects the one of the plurality of predefined criteria used by the determination unit on the basis of the estimation result of the complex environment estimation unit.