Title
Model-Based Threat Assessment In Semi-Autonomous Vehicles With Model Parameter Uncertainties
Abstract
In this paper, we consider model-based threat assessment methods which rely on vehicle and driver mathematical models and are based on reachability analysis tools and set invariance theory. We focus on the parametric uncertainties of the driver mathematical model and show how these can be accounted for in the threat assessment. The novelty of the proposed methods lies in the inclusion of the driver model uncertainties in the threat assessment problem formulation and in their validation through experimental data. We show how different ways of accounting for the model uncertainties impact the capabilities and the effectiveness of the proposed algorithms in detecting hazardous driving situations.
Year
DOI
Venue
2011
10.1109/CDC.2011.6161394
2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC)
Keywords
Field
DocType
approximation algorithms,invariance,classification algorithms,transportation,set theory,mathematical analysis,uncertainty,invariant theory,mathematical model,system theory
Set theory,Approximation algorithm,Mathematical optimization,Computer science,Reachability,Parametric statistics,Threat assessment,Novelty,Mathematical model,Statistical classification
Conference
ISSN
Citations 
PageRank 
0743-1546
2
0.50
References 
Authors
4
3
Name
Order
Citations
PageRank
Mohammad Ali1375.12
Paolo Falcone221724.97
Jonas Sjöberg362867.21