The BATmobile: Towards a Bayesian Automated Taxi
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Reasoning Under Uncertainty. Pages 1878-1884.
Abstract
The problem of driving an autonomous vehicle in normal traffic engages many areas of AI research and has substantial economic significance. We describe work in progress on a new approach to this problem that uses a decision-theoretic architecture using dynamic probabilistic networks. The architecture provides a sound solution to the problems of sensor noise, sensor failure, and uncertainty about the behavior of other vehicles and about the effects of one's own actions. We report on advances in the theory of inference and decision making in dynamic, partially observable domains. Our approach has been implemented in a simulation system, and the autonomous vehicle successfully negotiates a variety of difficult situations.
@inproceedings{ijcai1995p241,
title = {The BATmobile: Towards a Bayesian Automated Taxi},
author = {Forbes, Jeff and Huang, Timothy and Kanazawa, Keiji and Russell, Stuart J.},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {1878--1884},
year = {1995},
note = {Reasoning Under Uncertainty},
url = {https://ijcai.org/proceedings/1995/241},
}
TY - CPAPER TI - The BATmobile: Towards a Bayesian Automated Taxi AU - Forbes, Jeff AU - Huang, Timothy AU - Kanazawa, Keiji AU - Russell, Stuart J. T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 1878 EP - 1884 UR - https://ijcai.org/proceedings/1995/241 ER -Copied
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