Simulation-Based Robust Design of an Automatic Emergency Braking System Considering Sensor Measurement Errors

Michael Leyrer

ISBN 10: 334632768X / ISBN 13: 9783346327680

Published by GRIN Verlag, 2020

About this Item

Simulation-Based Robust Design of an Automatic Emergency Braking System Considering Sensor Measurement Errors | Michael Leyrer | Taschenbuch | Englisch | 2020 | GRIN Verlag | EAN 9783346327680 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 120092209

Bibliographic Details

• Title: Simulation-Based Robust Design of an Automatic Emergency Braking System Considering Sensor Measurement Errors
• Publisher: GRIN Verlag
• Publication Date: 2020
• Language: English
• ISBN 10: 334632768X
• ISBN 13: 9783346327680
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 5D millimeters 210 millimeters width by 148 millimeters height by 5 millimeters depth
• Weight: 90 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Bachelor Thesis from the year 2019 in the subject Electrotechnology, grade: 1.0, Technical University of Munich (Lehrstuhl für Methoden der Signalverarbeitung), course: Elektro- und Informationstechnik, language: English, abstract: Vehicular safety functions can increase driving safety by intervening in dangerous situations. However, as such functions rely on sensor measurements to decide actions, they are subject to sensor measurement errors which influence the performance. Therefore, a manufacturer has to design both the sensors and functions in a robust manner considering these errors. A methodology for such a robust design has already been proposed for an automatic emergency braking system and is based on a probabilistic quality measure. It is often only possible to evaluate the involved probabilities through simulations of the system at hand which can require enormous computational effort. The goal of this thesis is to find an efficient way of evaluating these probabilities based on simulations in order to reduce the computational effort.