eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. California Partners for Advanced Transit and Highways (PATH) UC Berkeley Title: Intelligent Diagnosis Based On Validated And Fused Data For Relilability And Safety Enhancement Of Automated Vehicles In An IVHS Author: Agogino, Alice Chao, Susan Goebel, Kai Alag, Satnam Cammon, Bradly Wang, Jiangxin Publication Date: 01-01-1998 Series: Research Reports Publication Info: Research Reports, California Partners for Advanced Transit and Highways (PATH), Institute of Transportation Studies, UC Berkeley Permalink: http://escholarship.org/uc/item/1mw2v298 Keywords: Automobiles--Automatic control--Mathematical models, Multisensor data fusion, Reliability (Engineering), Fault location (Engineering) Abstract: Vehicles in an IVHS system rely heavily on information obtained from sensors. So far, most control systems make the implicit assumption that sensor information is always correct. However, in reality, sensor information is always corrupted to some degree by noise which varies with operating conditions, environmental conditions, and other factors. In addition, sensors can fail due to a variety of reasons. To overcome these shortcomings, sensor validation is needed to assess the integrity of the sensor information and adjust or correct as appropriate. In the presence of redundant information, sensor data must be fused, accommodating the findings from the validation process. In this report, we address the above issues. Key words: sensor validation, sensor fusion, data fusion, supervisory control, management of uncertainty, reliability, safety, Bayes networks, fault detection, Diagnosis, Influence Diagrams, risk analysis, decision making