Autonomous Vehicle Occlusion Risk Maneuvering for Hidden Objects
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating roadways when they lack visibility due to occlusions, such as objects or road geometries, which can lead to uncertainty about the presence and movement of objects in occluded regions, resulting in unsafe situations.
Innovation Solution
The autonomous vehicle identifies occluded regions, hypothesizes the presence of objects, estimates their velocity and reaction, and performs driving maneuvers based on these assessments to ensure safe navigation, even in areas with limited visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AV remains stationary behind the occluding object until visibility is restored, then collision risk is reduced, but productivity deteriorates due to loss of time and inability to reach destination
Solution Approach 1:
The AV performs preliminary actions by planning and executing maneuvers around occluding objects before complete visibility is restored. The system uses sensor data from visible portions to predict occluded regions and proactively navigates around obstacles, rather than waiting passively for visibility to improve.
Solution Approach 2:
The AV uses sensor signals and computational models as intermediaries to perceive and navigate occluded regions. By processing sensor data to infer the presence and movement of objects in occluded areas, the system can make informed navigation decisions without direct visual confirmation.
2Productivity
If the AV enters the occluded region to reach destination, then productivity is improved, but reliability deteriorates due to increased collision risk
Solution Approach 1:
The AV continuously monitors sensor signals to detect objects entering or exiting occluded regions and uses this feedback to dynamically adjust navigation maneuvers. The system refines its understanding of occluded regions based on ongoing sensor data and updates its path planning accordingly.
Solution Approach 2:
The AV changes operational parameters such as velocity and position based on assessments of occluded region risk. The system adjusts its speed and trajectory to safely navigate around occluding objects while minimizing travel time, optimizing the balance between productivity and safety.
3Reliability
If the AV uses multiple sensors to improve visibility of occluded regions, then reliability is improved, but device complexity increases
Solution Approach 1:
The AV divides the environment into visible and occluded regions based on sensor data, and processes information from different sensor types to separately characterize each region. This segmentation allows the system to leverage multiple sensors effectively without overwhelming complexity.
Data Source
AI summary
An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.