## 1 Introduction  
In recent decades, the advancement of modern public transportation systems, such as metros and railways, has led to increasingly crowded transportation hubs teeming with a vast number of passengers carrying luggage, trolley cases, or suitcases [1]. Since luggage serves as a moving obstacle to surrounding passengers with a relatively high mass inertia, the presence of luggage-laden passengers can heavily impact evacuation efficiency during security emergencies such as fires and stampedes in transportation hubs [2]. Studying the dynamics of luggage-laden passengers can help in the development of automatic decision-making systems in public management [3, 4]. Most achievements focusing on luggage and passengers have uncovered the notable impact that luggage-laden passengers can have on emergency evacuation processes. Through field observations, studies have found that the walking speed of a luggage-laden passenger exhibits a distinct reduction compared to that of those not carrying luggage [5, 6, 7]. By investigating passenger flows in airport terminals, it was found that the size of the luggage actually affects the crowd distribution in building planes [8]. With the increase in the ratio of luggage carrying in bottleneck areas, evacuation efficiency can decrease, even resulting in evacuation failure [9]. These observation results preliminarily reveal how luggage affects normal crowd evacuation. The influence of wheeled luggage or trolley cases on the movement of surrounding passengers is complex. Factors such as the proportion and size of the luggage, the passenger density, and the dynamics of luggage's abnormal motions are crucial considerations [10]. Additionally, the presence of luggage leads much more frequently to collisions and friction for pedestrians in a crowd [11]. Traffic flow models have been applied to dense crowd modeling. In [12], a modified Aw-Rascle model was proposed to describe crowd convergence mechanisms, and it was found that internal pressure is positively correlated with velocity and density. However, since luggage is a moving obstacle, luggage-laden passengers and the surrounding passengers cannot be regarded as the same medium in a macroscopic view, and their interaction mechanisms cannot be described by conventional fluid models directly [13]. Moreover, [14] shows that the sway amplitude of luggage-laden passenger increases in highly dense pedestrian flows. As the wheeled luggage follows its owner with the help of a carry handle, the luggage will maintain a certain level of motion inertia during its movement. When its owner makes a sudden turn or sways, the suitcase will be driven by the passenger to turn, but the motion of the luggage experiences a certain lag following the passenger, which probably causes luggage drifting. Luggage drifting motion interferes with the expected movement of other passengers, and this crowd disturbance spreads out and dissipates with increasing time and distance [15]. Therefore, the mechanism of disturbance of luggage drifting on a crowd and the disturbance propagation dynamics are challenging issues for crowd safety, and are the primary focuses of this paper. To address the issues above, the main contributions of this study are as follows: (1) We propose a dynamic disturbance propagation model for abnormal luggage states based on the conservation law of fluid dynamics and the Aw-Rascle model. (2) As an obvious novelty, the disturbance effect of luggage on the surrounding passengers is transferred quantitatively into a nonlinear pressure term based on a contact model and pressure characteristics analysis. (3) Simulations of luggage drifting and retrograde disturbance are conducted to validate the effectiveness of the proposed disturbance propagation model. The numerical results display a more realistic dynamic process of the impact of luggage-laden passengers, and the values of disturbing forces and the density of passengers on both sides can help in crowd dynamics analysis.