Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Practical Solutions for Machine Learning Safety in Autonomous Vehicles   Autonomous vehicles rely on machine learning to solve challenging tasks in
perception and motion planning. However, automotive software safety standards
have not fully evolved to address the challenges of machine learning safety
such as interpretability, verification, and performance limitations. In this
paper, we review and organize practical machine learning safety techniques that
can complement engineering safety for machine learning based software in
autonomous vehicles. Our organization maps safety strategies to
state-of-the-art machine learning techniques in order to enhance dependability
and safety of machine learning algorithms. We also discuss security limitations
and user experience aspects of machine learning components in autonomous
vehicles.

15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn