Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Cooperative Optimal Control Framework for Connected and Automated
  Vehicles in Mixed Traffic Using Social Value Orientation   In this paper, we develop a socially cooperative optimal control framework
for connected and automated vehicles (CAVs) in mixed traffic using social value
orientation (SVO). In our approach, we formulate the interaction between a CAV
and a human-driven vehicle (HDV) as a simultaneous game to facilitate the
derivation of a Nash equilibrium. In the imposed game, each vehicle minimizes a
weighted sum of its egoistic objective and a cooperative objective. The SVO
angles are used to quantify preferences of the vehicles toward the egoistic and
cooperative objectives which lead to an appropriate design of weighting factors
in a multi-objective optimal control problem. We prove that by solving the
proposed optimal control problem, a Nash equilibrium can be obtained. To
estimate the SVO angle of the HDV, we develop a receding horizon estimation
based on maximum entropy inverse reinforcement learning. The effectiveness of
the proposed approach is demonstrated by numerical simulations at a highway
on-ramp merging scenario.

29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg