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DDT: Deep Driving Tree for Proactive Planning in Interactive Scenarios

Okamoto, Masaki and Perona, Pietro and Khiat, Abdelaziz (2018) DDT: Deep Driving Tree for Proactive Planning in Interactive Scenarios. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE , Piscataway, NJ, pp. 656-661. ISBN 978-1-7281-0321-1. http://resolver.caltech.edu/CaltechAUTHORS:20181213-145039837

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Abstract

We consider long-term planning problems for autonomous vehicles in complex traffic scenarios where vehicles and pedestrians interact. The decisions of an autonomous vehicle can influence surrounding other participants in these scenarios. Therefore, planning algorithms that preprocess the long-term prediction of other participants restrict freedom in action. In this paper, we process both problems of long-term planning and prediction at the same time. Our approach which we call DDT (Deep Driving Tree) is based on game tree accumulating a short-term prediction. Machine learning techniques are applied to this short-term prediction instead of model-based techniques that depends on domain knowledge. In contrast to Q-learning, this prediction part is trained off-line and does not require feedback from collision data. Our approach using a game tree models multiple future states of other participants to decide a proactive action taking uncertainties of their intentions into consideration. This approach is demonstrated in a left turning scenario at an intersection of left-hand traffic with oncoming vehicles without V2V communication.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/ITSC.2018.8569696DOIArticle
ORCID:
AuthorORCID
Perona, Pietro0000-0002-7583-5809
Additional Information:© 2018 IEEE.
Subject Keywords:Autonomous driving, intent estimation, machine learning, decision making
Record Number:CaltechAUTHORS:20181213-145039837
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181213-145039837
Official Citation:M. Okamoto, P. Perona and A. Khiat, "DDT: Deep Driving Tree for Proactive Planning in Interactive Scenarios," 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA, 2018, pp. 656-661. doi: 10.1109/ITSC.2018.8569696
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:91840
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:13 Dec 2018 23:00
Last Modified:13 Dec 2018 23:00

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