Heterogeneous vehicle platooning in mixed traffic: Modeling and analysis using Markov chains

To address the rigid dependence of conventional platooning strategies on the continuous distribution of connected and autonomous vehicles (CAVs), this study proposes a hybrid platooning strategy that allows human-driven vehicles (HVs) to join platoons via CAVs, thereby alleviating the applicability issue of existing strategies in mixed traffic scenarios. Under the proposed strategy, a Markov chain model is proposed to dynamically capture vehicle types, platoon structures, and platooning behaviors . Through theoretical analysis and numerical simulations, the performance of the hybrid platooning strategy is compared with that of conventional platooning strategies. When the CAV penetration rate ranges from 0.4 to 0.7, the proposed hybrid strategy improves traffic efficiency by 3.4% to 4.6% over the conventional platooning strategy. Under highly dispersed vehicle arrival sequences, it increases lane capacity by up to 14%. Moreover, when the maximum platoon length reaches 50, the hybrid platooning strategy yields a capacity improvement of 5.09%.