Segmented Cone Collision Risk Assessment
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Solution Overview
Problem
Current collision warning systems face challenges in processing large amounts of real-time data from various sources to accurately predict collisions and provide effective warnings, especially with the increasing sophistication of sensors and information about vehicle surroundings.
Innovation Solution
A dual-assessment system that uses a preliminary assessment mechanism for rapid geometric identification of potential accidents and a specialized assessment mechanism for detailed statistical analysis, employing geometric objects to estimate the probability and time of collisions, and determining a safe warning time based on user reaction and stopping capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sophisticated sensors and information processing are used to accurately predict collisions, then measurement precision and reliability are improved, but device complexity and information overload increase
Solution Approach 1:
The collision warning system is divided into two independent assessment mechanisms: a preliminary assessment mechanism that performs rapid geometric identification of potential accidents, and a specialized assessment mechanism that conducts detailed statistical analysis. This segmentation allows the system to process information efficiently at different stages, improving accuracy without overwhelming the system with complex simultaneous processing.
Solution Approach 2:
The preliminary assessment mechanism performs initial geometric identification of potential collision scenarios before the specialized assessment mechanism conducts detailed analysis. By performing preliminary filtering and identification first, the system reduces the volume of data that requires complex processing, thereby improving overall prediction accuracy while managing system complexity.
2Productivity
If real-time processing of large information flow is performed, then productivity and response speed are improved, but measurement precision and reliability may deteriorate due to information overload
Solution Approach 1:
The assessment process is segmented into two distinct stages: rapid geometric identification followed by detailed statistical analysis. This allows the system to quickly filter potential collisions in real-time while maintaining accuracy through subsequent detailed examination of identified scenarios.
Solution Approach 2:
The preliminary assessment mechanism performs rapid geometric identification of potential accidents before detailed analysis. This preliminary action filters out non-collision scenarios quickly, allowing the system to maintain real-time processing speed while ensuring accuracy through focused detailed assessment of only the most promising candidates.
3Reliability
If conservative collision assessment is performed, then reliability is improved, but loss of time occurs due to more thorough analysis
Solution Approach 1:
The system segments the assessment into two phases: a fast preliminary geometric assessment that provides immediate results, and a more time-consuming specialized statistical assessment that provides conservative reliable analysis only when needed. This segmentation ensures reliability through thorough analysis while minimizing time loss by limiting detailed analysis to specific cases.
Solution Approach 2:
The preliminary assessment performs rapid geometric identification before the conservative detailed assessment. This preliminary action filters scenarios so that time-consuming conservative analysis is applied only to potential collisions that pass the initial geometric test, thereby maintaining reliability while reducing overall assessment time.
Data Source
AI summary
One embodiment of the present invention provides a system that facilitates assessment of collision between a primary principal and a non-primary principal for early warning. During operation, the system receives information which indicates a state of the primary principal and a state of the non-primary principal. The system divides future time into a number of time intervals, and estimates a number of possible future states of the primary and non-primary principals, wherein each future state corresponds to a time interval. The system further represents the possible future states of the primary or non-primary principal as one or more geometric objects in a space of which at least one dimension indicates the time. In addition, the system determines a probability of collision between the primary and non-primary principals based on the geometric objects.