AR Collision Zone Projection for Vehicle Path Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle incident prediction systems lack the ability to provide detailed context about potential collisions, specifically indicating how detected obstructions may damage a vehicle if a predicted path is followed, which can lead to incidents even at slow speeds, and do not effectively enhance driver decision-making for incident avoidance.
Innovation Solution
A computer-implemented method that uses augmented reality to project incident information based on vehicle movements by determining a predicted path, identifying objects in the path, determining collision zones, and generating a display indicating potential damage, utilizing telemetry data, sensor data, and machine learning models to simulate collisions and update damage assessments in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current vehicle incident prediction systems detect obstructions and predict potential collisions, then incident prediction capability is improved, but detailed context about potential collision damage is not provided
Solution Approach 1:
The system segments the collision prediction information into multiple components: obstruction detection, predicted path determination, collision zone identification, and damage level assessment. Each component processes specific aspects of the potential incident independently, then integrates them to provide comprehensive context including visual overlays showing collision zones and damage projections on both the obstruction and vehicle.
Solution Approach 2:
The system adds a visual dimension to incident prediction by using augmented reality to overlay collision zone indicators and damage projections onto the driver's view of the real world. This transforms abstract prediction data into spatially contextualized visual information that shows exactly where and how damage might occur, adding depth and location context to the prediction.
2Ease of operation
If augmented reality display shows detailed collision zones and damage projections, then driver decision-making is enhanced, but system complexity increases
Solution Approach 1:
The augmented reality display system performs multiple functions simultaneously: it shows the predicted path, identifies obstruction locations, marks collision zones on both the vehicle and obstruction, and projects potential damage levels. This multi-functional approach consolidates what could be multiple separate systems into a single integrated display that provides comprehensive incident prediction information through one interface.
Solution Approach 2:
The system creates visual copies or representations of the collision zones and damage projections by overlaying graphical indicators onto the real-world view. These visual copies mirror the actual spatial relationships and potential impact areas, allowing the driver to see a replicated representation of the predicted incident superimposed on the real environment without adding physical complexity to the vehicle itself.
3Productivity
If the system provides real-time collision zone and damage level information, then incident avoidance is improved, but processing requirements increase
Solution Approach 1:
The system performs preliminary processing by determining the predicted vehicle path and identifying potential obstructions before a collision actually occurs. It pre-calculates collision zones and damage projections based on the current trajectory, allowing the driver to see potential incidents in advance and take preventive action. This preliminary assessment reduces the need for complex real-time processing during critical moments.
Solution Approach 2:
The system replaces complex mechanical collision testing and physical damage assessment with computational simulations and visual projections. Instead of requiring physical experiments or complex mechanical analysis to determine potential damage, the system uses software-based simulations that calculate damage levels virtually and display them as visual overlays, significantly reducing processing requirements compared to physical testing methods.
Data Source
AI summary
A computer-implemented method, a computer system and a computer program product project incident information within an augmented reality environment based on vehicle movements. The method includes determining a predicted path of a vehicle based on telemetry data associated with the vehicle. The method also includes obtaining driving conditions associated with a surrounding environment using a sensor. In addition, the method includes identifying an object in the predicted path of the vehicle. The method further includes determining a collision zone on the object and a corresponding collision zone on the vehicle based on physical attributes of the object and the predicted path of the vehicle. Lastly, the method includes generating a display of the driving conditions using an augmented reality device, where the display indicates the collision zone on the object and includes a virtual model of the vehicle that indicates the corresponding collision zone on the vehicle.