Autonomous Vehicle Collision Avoidance via Dynamic Object Classification
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating around unexpected dynamic objects, such as those with unpredictable movements, as existing systems struggle to accurately classify and respond to ballistic versus non-ballistic trajectories, leading to potential collisions.
Innovation Solution
The system detects dynamic objects, tracks their movement, classifies it as ballistic or non-ballistic, and determines if they are on a collision course, then implements a driving maneuver based on this classification to avoid the object, utilizing a combination of sensors and processing modules to assess and respond to the object's movement and size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the autonomous vehicle uses a computing system to navigate with minimal human input, then the ease of operation is improved, but the reliability deteriorates when unexpected dynamic objects are encountered
Solution Approach 1:
The system performs preliminary classification of dynamic objects into ballistic and non-ballistic categories before collision occurs. By pre-characterizing object movement patterns and predicting trajectories in advance, the system prepares appropriate response strategies, improving reliability when unexpected objects are encountered while maintaining autonomous operation.
2Measurement precision
If the vehicle encounters unexpected dynamic objects with unpredictable movements, then the adaptability deteriorates, but the need for sophisticated classification systems improves measurement precision requirements
Solution Approach 1:
The system segments dynamic objects into two distinct categories: ballistic objects (following predictable physics-based trajectories) and non-ballistic objects (exhibiting unpredictable movements). This segmentation allows the system to apply different response strategies tailored to each category, improving adaptability while maintaining high measurement precision for trajectory prediction and collision assessment.
3Measurement precision
If the system classifies object movement as ballistic or non-ballistic, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The system dynamically adjusts its classification and response based on real-time analysis of object movement characteristics. By continuously monitoring trajectory patterns and adapting the classification between ballistic and non-ballistic categories, the system achieves high measurement precision without requiring overly complex fixed-structure systems, allowing flexibility in handling diverse object types.
Data Source
AI summary
An autonomous vehicle may operate in an environment in which there is an unexpected dynamic object. The autonomous vehicle can detect the dynamic object. The dynamic object can have an associated movement. The movement of the dynamic object can be tracked. The movement of the dynamic object can be classified as being one ballistic or non-ballistic. It can be determined whether the dynamic object is on a collision course with the autonomous vehicle. Responsive to determining that the dynamic object is on a collision course with the autonomous vehicle, a driving maneuver for the autonomous vehicle can be determined. The driving maneuver can be based at least in part on the movement of the dynamic object. The autonomous vehicle can be caused to implement the determined driving maneuver.