Vehicle Type Specific Waypoint Generation

We develop a generic mechanism for generating vehicle-type specific sequences of waypoints from a probabilistic foundation model of driving behavior. Many foundation behavior models are trained on data that does not include vehicle information, which limits their utility in downstream applications s...

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Bibliographic Details
Main Authors: Liu, Yunpeng, Lavington, Jonathan Wilder, Scibior, Adam, Wood, Frank
Format: Conference Proceeding
Language:English
Subjects:
Behavioral sciences
Data models
Planning
Prediction algorithms
Predictive models
Probabilistic logic
Reinforcement learning
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Summary:We develop a generic mechanism for generating vehicle-type specific sequences of waypoints from a probabilistic foundation model of driving behavior. Many foundation behavior models are trained on data that does not include vehicle information, which limits their utility in downstream applications such as planning. Our novel methodology conditionally specializes such a behavior predictive model to a vehicle-type by utilizing byproducts of the reinforcement learning algorithms used to produce vehicle specific controllers. We show how to compose a vehicle specific value function estimate with a generic probabilistic behavior model to generate vehicle-type specific waypoint sequences that are more likely to be physically plausible then their vehicle-agnostic counterparts.
ISSN:2153-0866
DOI:10.1109/IROS47612.2022.9981421