Road Agent Behavior Prediction Using Intermediate Intention Signals
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately predicting the intentions and behaviors of nearby agents, such as pedestrians and vehicles, which can lead to delayed decision-making and increased computational complexity due to the need for high-resolution sensor data processing.
Innovation Solution
Implementing separate intention prediction models that generate intention signals, which are then used by behavior prediction models to forecast agent behaviors, reducing the computational burden and latency by avoiding the processing of high-resolution sensor data directly within the behavior prediction subsystem.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution sensor data is processed directly within the behavior prediction subsystem, then prediction accuracy may be improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The system divides the prediction task into two separate subsystems: an intention prediction subsystem that processes high-resolution sensor data to generate intention signals, and a behavior prediction subsystem that uses these signals along with lower-resolution data to predict behaviors. This segmentation allows each subsystem to operate with appropriate data resolution, reducing overall computational complexity while maintaining prediction accuracy.
Solution Approach 2:
The patent introduces intention signals as an intermediary representation between sensor data and behavior predictions. These intention signals serve as a compressed, semantically meaningful intermediate form that captures essential agent intentions without requiring the behavior prediction subsystem to process raw high-resolution sensor data directly, thereby reducing computational burden.
2Measurement precision
If high-resolution sensor data is processed directly within the behavior prediction subsystem, then prediction accuracy may be improved, but processing time increases due to latency
Solution Approach 1:
By segmenting the processing pipeline into intention prediction and behavior prediction stages with different data resolution requirements, the system enables parallel processing paths. The intention prediction subsystem processes high-resolution data independently while the behavior prediction subsystem operates with lower-resolution data, reducing overall processing time and latency.
Solution Approach 2:
The system performs preliminary intention prediction processing before behavior prediction. By pre-computing intention signals from sensor data in advance, the behavior prediction subsystem receives ready-to-use intermediate results, eliminating the need to re-process high-resolution sensor data and reducing processing latency.
3Adaptability or versatility
If a single integrated perception model is used for both intention and behavior prediction, then model versatility is maintained, but training complexity and human effort increase
Solution Approach 1:
The patent separates the perception models into distinct intention prediction models and behavior prediction models. Each model is specialized for its specific task and can be trained independently using appropriate training data and metrics, reducing training complexity while maintaining overall system versatility through the coordinated operation of multiple specialized models.
Data Source
AI summary
An autonomous vehicle includes sensor subsystem(s) that output a sensor signal. A perception subsystem (i) detects an agent in a vicinity of the autonomous vehicle and (ii) generates a motion signal that describes at least one of a past motion or a present motion of the agent. An intention prediction subsystem processes the sensor signal to generate an intention signal that describes at least one intended action of the agent. A behavior prediction subsystem processes the motion signal and the intention signal to generate a behavior prediction signal that describes at least one predicted behavior of the agent. A planner subsystem processes the behavior prediction signal to plan a driving decision for the autonomous vehicle.