Vehicle following dynamics model for curves incorporating cross slope angle with applicability to straight and transition curve

Abstract The stability of traffic flow has long been a research focus in transportation. Car-following studies, which simulate the dynamic behavior of vehicles within traffic streams, aim to improve the efficiency and stability of traffic flow, thereby enhancing the overall performance of transportation systems. However, most scholarly research on car-following focuses on straight roads, with studies on curved roads often neglecting the impact of the cross-slope. In real-world traffic, curved road scenarios are an indispensable component, and the common alignments connecting modern expressways to ramps, which are composed of straight segments, transition curves (clothoids), and circular curves, pose even greater challenges to car-following behavior due to their complex dynamic characteristics and spatial limitations. This paper aims to develop a curve car-following model applicable to these distinct road geometries (straight roads, transition curves, and circular curves) by comprehensively incorporating factors such as curve radius, superelevation angle, maximum speed decision-making, and a dynamic look-ahead mechanism. Furthermore, the study investigates the influence of varying curve parameters on vehicle car-following dynamics. The proposed model’s effectiveness is validated through simulation experiments. A sensitivity analysis is also performed on key parameters, including superelevation angle, friction coefficient, and look-ahead coefficients. The results indicate that this model exhibits enhanced stability and safety in curved road environments and can adaptively manage the transition from straight segments to curves. This research contributes to the optimization of curve design, enhancing the stability and traffic efficiency of vehicular flow in curved road segments.