Lateral Influence on Capacity Adjustment of Lanes Number for Mixed Autonomous Vehicles

Capacity is a fundamental concept in transportation engineering that serves as the objective for traffic planning, management, and control. The evaluation of capacity is typically quantified using the capacity adjustment factor (CAF), which captures the influence of various factors on the base capacity. With the emergence of autonomous vehicles, the reevaluation of CAF has become increasingly indispensable. One crucial influencing factor is the number of lanes, and its impact on capacity may vary between mixed flows of autonomous and human-driven vehicles. This chapter focuses on developing the CAF based on models established in previous chapters. To achieve this, a stochastic multi-lane microscopic traffic flow model is developed, incorporating a formulation for the repulsive force between neighboring lanes. Simulation experiments are conducted to assess capacity under different settings, such as varying lane numbers and market penetration rates. The results reveal that the lateral noise, a product of the stochastic nature of the model, cannot be overlooked in capacity evaluations. This finding emphasizes the importance of considering lateral influences when evaluating capacity, particularly in the context of mixed autonomous and human-driven vehicle flows. The outcomes of this study contribute to a more comprehensive understanding of capacity dynamics, supporting informed decision-making in traffic planning and management.