Feasibility Study Of Fully Autonomous Vehicles Using Decision-theoretic Control

This project studied the feasibility of constructing an autonomous vehicle controller based on probabilistic inference and utility maximization. Several theoretical and algorithmic advances were required in order to create an inference system capable of handling vehicle monitoring in a real-time fashion. New methods were also developed for learning probabilistic models from data, and for learning control policies given reward/penalty feedback.

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Year of publication:	1997-01-01
Authors:	Forbes, Jeffrey ; Et. al.
Institutions:	Institute for Transportation Studies (ITS), University of California-Berkeley
Subject:	Automobiles-Automatic control \| Bayesian statistical decision theory \| Real-time control

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Extent:	application/pdf
Series:	Institute of Transportation Studies, Research Reports, Working Papers, Proceedings.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series Institute of Transportation Studies (UCB)
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010536761