Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Sensor Fusion Method using Dynamic Bayesian Network for Precise
  Vehicle Localization and Road Matching   This paper presents a multi-sensor fusion strategy for a novel road-matching
method designed to support real-time navigational features within advanced
driving-assistance systems. Managing multihypotheses is a useful strategy for
the road-matching problem. The multi-sensor fusion and multi-modal estimation
are realized using Dynamical Bayesian Network. Experimental results, using data
from Antilock Braking System (ABS) sensors, a differential Global Positioning
System (GPS) receiver and an accurate digital roadmap, illustrate the
performances of this approach, especially in ambiguous situations.

28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th