Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A system of vision sensor based deep neural networks for complex driving
  scene analysis in support of crash risk assessment and prevention   To assist human drivers and autonomous vehicles in assessing crash risks,
driving scene analysis using dash cameras on vehicles and deep learning
algorithms is of paramount importance. Although these technologies are
increasingly available, driving scene analysis for this purpose still remains a
challenge. This is mainly due to the lack of annotated large image datasets for
analyzing crash risk indicators and crash likelihood, and the lack of an
effective method to extract lots of required information from complex driving
scenes. To fill the gap, this paper develops a scene analysis system. The
Multi-Net of the system includes two multi-task neural networks that perform
scene classification to provide four labels for each scene. The DeepLab v3 and
YOLO v3 are combined by the system to detect and locate risky pedestrians and
the nearest vehicles. All identified information can provide the situational
awareness to autonomous vehicles or human drivers for identifying crash risks
from the surrounding traffic. To address the scarcity of annotated image
datasets for studying traffic crashes, two completely new datasets have been
developed by this paper and made available to the public, which were proved to
be effective in training the proposed deep neural networks. The paper further
evaluates the performance of the Multi-Net and the efficiency of the developed
system. Comprehensive scene analysis is further illustrated with representative
examples. Results demonstrate the effectiveness of the developed system and
datasets for driving scene analysis, and their supportiveness for crash risk
assessment and crash prevention.

9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat