Real-Time Predictive Modeling and Robust Avoidance of Pedestrians with Uncertain, Changing Intentions
To plan safe trajectories in urban environments, autonomous vehicles must be able to quickly assess the future intentions of dynamic agents. Pedestrians are particularly challenging to model, as their motion patterns are often uncertain and/or unknown a priori. This paper presents a novel changepoin...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer
2017
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| Online Access: | http://hdl.handle.net/1721.1/106305 https://orcid.org/0000-0001-8576-1930 |