Development of a car-following model incorporating the oppression effects of large trucks

The presence of large trucks on highways significantly alters the driving behavior of surrounding vehicles, especially by disrupting the car-following patterns of smaller vehicles due to their size, speed differences, and visibility constraints. This study focuses on investigating the mechanism of how large trucks on highways impact the car-following behavior of surrounding drivers. The research begins by utilizing unmanned aerial vehicles (UAV) to collect vehicle trajectory data. A novel concept, termed the “oppression effects” of large trucks, is introduced, and its influence is characterized using potential field theory. Subsequently, a car-following model is developed that incorporates the oppression effects of large trucks. To illustrate the distribution of these effects, intensity contour maps are employed based on various motion states of the large truck. Finally, the proposed model is then calibrated using real-world trajectory data, and its predictive accuracy is assessed against benchmark car-following models. The proposed model improves trajectory prediction accuracy by over 40.9 % in RMSE and 22.4 % in MAE compared to classical models. The results demonstrate that the car-following model, which accounts for the oppression effects of large trucks, yields more accurate predictions of the driving behavior of vehicles following large trucks on highways. This research contributes to the theoretical foundation for behavior modeling and risk control in mixed traffic environments involving trucks and cars, ultimately enhancing safety for drivers in proximity to large trucks.