Pedestrian Safety by Intent Prediction: A Lightweight LSTM-Attention Architecture and Experimental Evaluations with Real-World Datasets
Author:
Affiliation:
1. University of California,Laboratory for Intelligent & Safe Automobiles (LISA),San Diego,La Jolla,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10587320/10588370/10588868.pdf?arnumber=10588868
Reference23 articles.
1. National highway traffic safety administration (nhtsa). traffic safety facts 2020
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3. Safe control transitions: Machine vision based observable readiness index and data-driven takeover time prediction;Greer
4. Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior
5. PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction
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