## 1 Introduction  
Toll roads provide a great convenience in the road transportation system. In China, toll collection mainly relies on the toll plazas; they are a crucial component of toll roads. By the end of 2021, the quantity of toll plazas in China had increased to 972 [1]. Since electronic payments have not been fully popularized yet, the majority of toll plazas in China are traditional mainline toll plaza (TMTPs), which consist of both electronic toll collection (ETC) and manual toll collection (MTC) methods. In the TMTP, drivers using electronic payment can pass through the ETC lanes at low speeds (20 km/h in China), but those paying with cash must stop at MTC lanes to finish the payment. Previous research has shown that there is a considerable speed differential between ETC and MTC vehicles in the diverging area of toll plazas [2]. However, vehicles with different toll collection types are not restricted by lane markings or separation facilities in the diverging area of the TMTP. Vehicles need to complete the diversion and select their matching toll collection lanes within a limited distance. Complex distribution of toll collection lanes and speed difference of ETC and MTC vehicles result in the diverging area becoming a hot spot of frequent crossing behaviors and rapid decelerations [3; 4; 5; 6]. These aggressive driving behaviors caused a large number of conflicts [2; 7]. There is an urgent need to explore the conflict mechanism in the diverging area of toll plazas so a corresponding effective policy can be developed. Modeling the relationship between traffic conflict risk and contributing factors can help us understand how these factors cause conflict risks [8; 9; 10]. Numerous robust econometric models have been employed to investigate the possible association between conflict risk and influencing factors. Nevertheless, there may be some unobserved and unmeasured heterogeneity variables that make the existing factors less effective in explaining the observed results [11; 12]. Especially on complex road nodes like toll plazas, drivers need to process more information simultaneously than on the road sections, such as choosing a matching toll lane with shorter waiting time. Ignoring such heterogeneity and assuming the effect of a contributing factor across all observations as the same will lead to biased and incorrect parameter estimation [13]. The random parameter approach is applied to solve the problem of unobserved heterogeneity. As one of the random parameter approaches, the heterogeneity in the means and variances of the random parameters has been used to explore the mechanism of crash frequency and severity and obtained remarkable results [14; 15; 16; 17]. In previous studies, the safety analysis of toll plazas is mainly based on historical crash data [18; 19]. However, due to their insufficient quantity, crash data need to be collected for a long time before they can be used for analysis. Meanwhile, since most traffic conflicts have not further developed to crashes, it is not comprehensive to judge the traffic safety status of a region based only on crash data. With the development of information techniques, a growing number of devices are used to record vehicle traveling information, such as GPS, high-definition cameras, and unmanned aerial vehicles (UAVs). Vehicles' high-precision trajectory data are extracted in large quantities and are being utilized more frequently to analyze traffic safety. Potential conflicts captured from trajectory data overcome the limitation of insufficient quantity and incomplete assessment of historical crash data. This study analyzes the characteristics of conflicts in the toll plaza diverging area based on the trajectory data collected by UAV. Although several studies have assessed toll plaza conflict risks based on trajectory data [2; 5; 7], they do not consider the conflict characteristics and influencing mechanism between vehicles with different toll collection types.