Recent advances and trends in on-board embedded and networked automotive systems

LL Bello, R Mariani, S Mubeen… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Modern cars consist of a number of complex embedded and networked systems with
steadily increasing requirements in terms of processing and communication resources …

Software verification and validation of safe autonomous cars: A systematic literature review

N Rajabli, F Flammini, R Nardone, V Vittorini - IEEE Access, 2020 - ieeexplore.ieee.org
Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …

Artificial intelligence applications in the development of autonomous vehicles: A survey

Y Ma, Z Wang, H Yang, L Yang - IEEE/CAA Journal of …, 2020 - ieeexplore.ieee.org
The advancement of artificial intelligence (AI) has truly stimulated the development and
deployment of autonomous vehicles (AVs) in the transportation industry. Fueled by big data …

Safely entering the deep: A review of verification and validation for machine learning and a challenge elicitation in the automotive industry

M Borg, C Englund, K Wnuk, B Duran… - arXiv preprint arXiv …, 2018 - arxiv.org
Deep Neural Networks (DNN) will emerge as a cornerstone in automotive software
engineering. However, developing systems with DNNs introduces novel challenges for …

Algorithm and hardware implementation for visual perception system in autonomous vehicle: A survey

W Shi, MB Alawieh, X Li, H Yu - Integration, 2017 - Elsevier
This paper briefly surveys the recent progress on visual perception algorithms and their
corresponding hardware implementations for the emerging application of autonomous …

Testing, validation, and verification of robotic and autonomous systems: a systematic review

H Araujo, MR Mousavi, M Varshosaz - ACM Transactions on Software …, 2023 - dl.acm.org
We perform a systematic literature review on testing, validation, and verification of robotic
and autonomous systems (RAS). The scope of this review covers peer-reviewed research …

Development methodologies for safety critical machine learning applications in the automotive domain: A survey

M Rabe, S Milz, P Mader - … of the IEEE/CVF Conference on …, 2021 - openaccess.thecvf.com
Enabled by recent advances in the field of machine learning, the automotive industry pushes
towards automated driving. The development of traditional safety-critical automotive …

A Stochastic Approach to Classification Error Estimates in Convolutional Neural Networks

J Peleska, F Brüning, M Gleirscher… - arXiv preprint arXiv …, 2023 - arxiv.org
This technical report presents research results achieved in the field of verification of trained
Convolutional Neural Network (CNN) used for image classification in safety-critical …

Probabilistic risk assessment of an obstacle detection system for goa 4 freight trains

M Gleirscher, AE Haxthausen, J Peleska - Proceedings of the 9th ACM …, 2023 - dl.acm.org
We propose a quantitative risk assessment approach for the design of an obstacle detection
function for low-speed freight trains with grade of automation 4. In this five-step approach …

Department of Electrical and Computer Engineering

G Liu - Rutgers University, private communication (10 …, 2010 - library-archives.canada.ca
Abstract In Multiple-Input Multiple-Output (MIMO) broadcast channels, the multi-
antennabasestation transmits information to multiple non-cooperative mobile users …