9. Stochastic Lateral Wandering Patterns of Mixed Traffic Flow

The rise of autonomous vehicles has raised concerns about the suitability of current infrastructure, originally designed for human-driven vehicles. One critical issue is the impact of autonomous vehicles’ lateral movement on the fatigue of pavements, as they tend to focus on the lane middle line. However, as the market penetration of autonomous vehicles gradually increases, the distribution of their lateral movement within the mixed flow of vehicles remains uncertain. This chapter aims to investigate the spatial distribution of vehicle locations, taking into account the varying ratio of autonomous vehicles. To achieve this goal, we first analyze the factors influencing lateral movement, including forces from lane boundaries, lane markings, neighboring vehicles, and stochastic noise. Subsequently, we develop a stochastic model to capture the lateral movement of autonomous vehicles. By utilizing the lateral control mechanisms employed by autonomous vehicles, we derive a stochastic model specifically tailored to their lateral behavior. The overall lateral distribution is obtained by weighting the combinations of vehicle types across all lanes. The results demonstrate that our proposed model consistently aligns with existing recommendations and accurately captures the changes in lateral distribution. This research contributes to a better understanding of the potential impacts of autonomous vehicles on our road infrastructure and can provide valuable insights for planning and design purposes.