Work

Safety analysis of Autonomous Ground Vehicle optical systems: Bayesian belief networks approach

Year: 2013

Type: conference-paper

Abstract: Autonomous Ground Vehicles (AGV) require diverse sensor systems to support the navigation and sense-and-avoid tasks. Two of these systems are discussed in the paper: dual camera-based computer vision (CV) and laser-based detection and ranging (LIDAR). Reliable operation of these optical systems is critical to safety since potential faults or failures could result in mishaps leading to loss of life and property. The paper identifies basic hazards and, using fault tree analysis, the causes and effects of these hazards as related to LIDAR and CV systems. A Bayesian Belief Network approach (BN) supported by automated tool is subsequently used to obtain quantitative probabilistic estimation of system safety.

Source: Annals of Computer Science and Information Systems

Authors: Daniel Reyes Duran, Elliot Robinson, Andrew J. Kornecki, Janusz Zalewski

Institutions: Embry-Riddle Aeronautical University Daytona Beach Florida Campus, Embry–Riddle Aeronautical University, Florida Gulf Coast University

Language: English

Topic: Risk and Safety Analysis

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W1505408913

FWCI: 1.878

Cites: 6

Cited by: 14

Related to: 10