Vehicle Platooning Control With Video-Based Trajectory Feedback
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Solution Overview
Problem
Current autonomous driving systems face challenges in maintaining stable and efficient platooning by accurately controlling the distance and trajectory of vehicles, especially when external factors like separate vehicles cutting in or out of the formation occur.
Innovation Solution
An apparatus and method utilizing reinforcement learning based on video information and control points to control the driving trajectory of a host vehicle, generating feedback signals to adjust the driving speed and steering of the host vehicle to maintain a stable platooning formation, even when separate vehicles intervene.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If reinforcement learning is used to control platooning, then the autonomous vehicle can take optimal actions during platooning, but the system complexity increases due to the need for processing video information and generating feedback signals
Solution Approach 1:
The patent implements a feedback mechanism where the reward determination part generates feedback signals by comparing the actual position of the rear vehicle with the desired position based on control points. This feedback is used by the learning device to continuously optimize the platooning control strategy, enabling autonomous adaptation while maintaining manageable system complexity through structured information processing.
Solution Approach 2:
The system segments the platooning control task into distinct functional modules: video information processing, control point generation, reward determination, and reinforcement learning. This segmentation allows each module to handle specific aspects of the control problem independently, reducing overall system complexity while achieving sophisticated autonomous platooning control.
2Measurement precision
If the system uses video information and control points for trajectory control, then the rear vehicle can follow the host vehicle's trajectory accurately, but the measurement and detection difficulty increases
Solution Approach 1:
The patent introduces control points as intermediary elements that mediate between the host vehicle's trajectory and the rear vehicle's following behavior. Instead of directly processing complex video information to determine following actions, the system generates simplified control points that represent key trajectory features, making measurement and detection more manageable while maintaining high trajectory following accuracy.
3Stability of the object's composition
If the system manages platooning formation with multiple vehicles, then the platooning stability improves, but the device complexity increases due to coordinate comparison and feedback signal generation
Solution Approach 1:
The reward determination part serves multiple functions: it compares coordinates, generates feedback signals, determines rewards for reinforcement learning, and adapts to different platooning scenarios including cut-in and cut-out events. This multi-functionality maintains platooning formation stability across various situations without proportionally increasing device complexity, as the same core mechanism handles diverse control requirements.
Data Source
AI summary
Proposed are apparatus and control method for platooning, the apparatus including a learning device which performs reinforcement learning based on a feedback signal and video information and controls driving of a host vehicle based on a result of the reinforcement learning such that a rear vehicle can follows a driving trajectory of the host vehicle, and a reward determination part which generates the feedback signal by comparing coordinates of the rear vehicle with coordinates of control points for the driving trajectory of the host vehicle.