Markov chain-based capacity modeling for mixed traffic flow with bi-class connected vehicle platoons on minor road at priority intersections

Priority intersections, as one of typical unsignalized intersections, are devised to allocate the right of way to vehicles on major road, requiring vehicles on minor road waiting for a safe gap before passing through intersections. Thus, capacity of minor road plays an important role in determining the efficiency of priority intersections. With connectivity features, both connected automated vehicles (CAVs) and connected vehicles (CVs) have the potential to form platoons which are referred to as connected vehicle platoons, thereby improving capacity of mixed traffic with regular vehicles (RVs) on minor road at priority intersections. This paper proposes a capacity model for mixed traffic with the aforementioned bi-class connected vehicle platoons at priority intersections. To begin with, eleven states of following headway in mixed traffic flow were defined to mathematically derive the capacity modeling based on Markov chain theory. The proposed capacity model incorporated the average occupation time and lost time of vehicles on minor road at priority intersections. We then presented an analytical framework of optimization designs for platoon operations of both CAVs and CVs, including the maximum platoon size and platooning willingness, to achieve capacity improvement in mixed traffic scenarios. Finally, numerical experiments were conducted to verify the effectiveness of the proposed model. The results demonstrate that the proposed model can be used for quantitatively calculating mixed traffic capacity on minor road at priority intersections, under the influence of both CAV/CV maximum platoon size and platooning willingness. Following the analytical framework, optimal values of CAV/CV maximum platoon size and platooning willingness can be determined under varying penetration rates for mixed traffic capacity improvement.