Predictive Turning Assistant Using AI Object Trajectory Prediction
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Solution Overview
Problem
Vehicles, both manually and autonomously driven, face risks during turns due to unawareness of potential hazards, highlighting the need for a secure method to manage turns.
Innovation Solution
A method involving detection of upcoming turns, sensing of the environment, application of artificial intelligence to predict object movements, and adaptive path adjustment or alerting mechanisms to mitigate collision risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle performs turns without advance detection and prediction systems, then the device complexity is reduced, but the safety and reliability during turns deteriorates due to unawareness of potential hazards
Solution Approach 1:
The system performs preliminary detection of turns using map data and current location information before the vehicle reaches the turn. It then pre-activates sensors to detect objects in the turn area and uses AI to predict object movements during the upcoming turn, allowing the vehicle to prepare for potential hazards in advance rather than reacting after they are detected
Solution Approach 2:
The safety system is divided into distinct functional modules: turn detection module (using map and location data), sensor activation module, object detection module (using various sensors), AI prediction module (for predicting object movements), and path adjustment module. This segmentation allows each module to perform its specific function efficiently while maintaining overall system reliability
2Reliability
If the vehicle uses advanced sensors and AI prediction systems to detect objects and predict movements, then the safety during turns is improved, but the loss of time for processing and responding increases
Solution Approach 1:
The system activates sensors and performs AI predictions in advance during the approach to a turn, not when the turn is imminent. By using map data to identify upcoming turns and activating the full detection and prediction system beforehand, the vehicle processes information during the approach phase rather than during the critical turning moment, reducing response time loss
Solution Approach 2:
The system periodically activates sensors and performs AI predictions at specific intervals based on the vehicle's approach to detected turns from map data. Rather than continuous operation, the system engages detection and prediction functions at strategic moments when turns are anticipated, optimizing the balance between safety and time efficiency
3Reliability
If the vehicle adjusts its path adaptively during turns based on detected objects and predicted movements, then the safety is improved, but the device complexity increases due to path calculation and control systems
Solution Approach 1:
The path adjustment capability is implemented as a dynamic system that can modify the vehicle's predefined path in real-time based on detected objects and AI-predicted movements. The system calculates alternative paths and executes adjustments during turns, transitioning from a static predefined path to a dynamic adaptive path that responds to environmental conditions
Solution Approach 2:
The AI prediction system acts as an intermediary between object detection and path adjustment. Rather than directly controlling path changes based on raw sensor data, the AI prediction layer processes object movements and generates predictions about future positions, providing refined input to the path calculation system and simplifying the overall control architecture
Data Source
AI summary
A method for assisting in turning a vehicle, the method may include detecting or estimating that the vehicle is about to turn to a certain direction or is turning to the certain direction; sensing a relevant portion of an environment of the vehicle to provide sensed information, wherein the relevant portion of the environment is positioned at a side of the vehicle that corresponds with the certain direction; applying an artificial intelligence process on the sensed information to (i) detect objects within the relevant portion of the environment and (ii) estimate expected movement patterns of the objects within a time frame that ends with an expected completion of the turn of the vehicle; determining, given an expected trajectory of the vehicle during the turn and the expected movement patterns of the objects, whether at least one of the objects is expected to cross the trajectory of the vehicle during the turn; and responding to an outcome of the determining.