  Due to the rapid growth of data transmissions in internet of vehicles (IoV),
finding schemes that can effectively alleviate access congestion has become an
important issue. Recently, many traffic control schemes have been studied.
Nevertheless, the dynamics of traffic and the heterogeneous requirements of
different IoV applications are not considered in most existing studies, which
is significant for the random access resource allocation. In this paper, we
consider a hybrid traffic control scheme and use proximal policy optimization
(PPO) method to tackle it. Firstly, IoV devices are divided into various
classes based on delay characteristics. The target of maximizing the successful
transmission of packets with the success rate constraint is established. Then,
the optimization objective is transformed into a markov decision process (MDP)
model. Finally, the access class barring (ACB) factors are obtained based on
the PPO method to maximize the number of successful access devices. The
performance of the proposal algorithm in respect of successful events and delay
compared to existing schemes is verified by simulations.
