Dealing with uncertainty in perception system for the characterization of driving situation

Author

Cherfaoui, Veronique ; Burie, Jean-Christophe ; Royére, Cyril ; Gruyer, Dominique

Author_Institution

Univ. de Technol. de Compiegne, France

fYear

2000

fDate

2000

Firstpage

83

Lastpage

88

Abstract

Situation characterization requires numerous data in order to recognize real driving situation. The quality of data is important to assume the quality of situation recognition and characterization. The aim of this work is to describe imperfections in sensor data processing and their implications in decision processing. Expected results are a granularity definition to model and propagate imperfection. In this paper we focus on uncertainty characterization deriving from the reliability and confidence in sensors and data processing

Keywords

computer vision; data analysis; information theory; optical tracking; road traffic; traffic engineering computing; uncertainty handling; CASSICE project; Dampster Shafer theory; data reliability; decision processing; driving situation; perception system; road traffic; sensor data processing; situation characterization; uncertainty handling; vehicle tracking; Character recognition; Computer vision; Data processing; Machine vision; Object detection; Psychology; Sensor phenomena and characterization; Uncertainty; Vehicle detection; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Transportation Systems, 2000. Proceedings. 2000 IEEE

Conference_Location

Dearborn, MI

Print_ISBN

0-7803-5971-2

Type

conf

DOI

10.1109/ITSC.2000.881022

Filename

881022