Autonomous Vehicle Behavior Modeling for Predicting Surrounding Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles lack effective methods to predict the behavior of surrounding objects, such as pedestrians and vehicles, which can lead to accidents and inefficient travel due to the limitations of existing sensing and control systems.
Innovation Solution
A server-based system that analyzes data from various sources to create and update behavior models for detected objects, allowing autonomous vehicles to predict their movements and adjust their control strategies accordingly, using world-view and actions-of-interest data to improve safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If autonomous vehicles use basic sensing systems to detect surrounding objects, then the system complexity is reduced, but the ability to accurately predict object behavior deteriorates
Solution Approach 1:
The patent introduces a server as an intermediary component that receives sensor data from autonomous vehicles, creates behavior models for detected objects, and sends predictions back to vehicles. This mediator handles the complex behavior analysis externally, allowing the vehicle's onboard sensing system to remain relatively simple while achieving high prediction accuracy through the server's sophisticated modeling capabilities.
2Measurement precision
If autonomous vehicles collect and analyze extensive world-view and actions-of-interest data, then behavior prediction accuracy is improved, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary data processing and behavior model creation on the server before the autonomous vehicle needs the predictions. The server pre-analyzes world-view data and actions-of-interest data to create behavior models in advance, so that when the vehicle queries for predictions, the analysis is already complete or near-complete, minimizing the time the vehicle experiences during critical decision-making moments.
Solution Approach 2:
The server continuously receives and processes data from multiple vehicles, maintaining ongoing behavior models that are continuously updated with new information. This continuous processing allows the system to accumulate insights over time without interrupting vehicle operations, as the server works continuously in the background while vehicles operate in real-time.
3Stability of the object's composition
If a centralized server creates and manages behavior models for all vehicles, then behavior prediction consistency across the fleet is improved, but the device complexity of the server system increases
Solution Approach 1:
The centralized server is designed to serve multiple autonomous vehicles simultaneously, creating and managing behavior models that are universally applicable across the entire vehicle fleet. This multi-functional approach allows the server to handle data from numerous vehicles, generate standardized behavior models, and provide predictions to all vehicles, ensuring consistency across the fleet while amortizing the complexity across many users.
Data Source
AI summary
A method and apparatus are provided for determining one or more behavior models used by an autonomous vehicle to predict the behavior of detected objects. The autonomous vehicle may collect and record object behavior using one or more sensors. The autonomous vehicle may then communicate the recorded object behavior to a server operative to determine the behavior models. The server may determine the behavior models according to a given object classification, actions of interest performed by the object, and the object's perceived surroundings.