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Efficient resource allocation strategies are pivotal in vehicular communications as connected devices steeply increase in scenarios with much more stringent requirements. In this work, we propose a DRL-based sequential scheduling approach for sum-rate maximization in the uplink of IRS-assisted MU MIMO vehicular communications. We formulate the scheduling task as a partially observable Markov decision process (POMDP) and propose a novel stream-level sequential solution based on the PPO algorithm. We consider a realistic imperfect channel state information (ICSI) model and assess the proposal in several communication setups comprising both spatially uncorrelated and correlated links. Simulation results show that the proposed DRL-based sequential scheduling approach is a robust alternative to more computationally demanding benchmarks.