# A Collision Risk Assessment Method for Aircraft on the Apron Based on Petri Nets
## 2 Background of the Study
(2017), considering the blind spots in the vision of tow tractor drivers and the unique characteristics of towing vehicles, developed an aircraft collision avoidance model for airport aprons. The model enables the measurement of aircraft posture and position, allowing for collision prevention functionalities. In the field of airport operational safety assessment, scholars have primarily focused on establishing evaluation index systems that influence operational safety. For instance, [PERSON] et al. [PERSON] et al. (2018) developed a safety performance index system to assess airport operational safety risks, using actual airport operational data to validate the feasibility of the model. [PERSON] et al. [PERSON] et al. (2019) analyzed the risk factors influencing the aircraft turnaround process and developed a risk assessment model. This model was used to evaluate the current risk conditions at airports, demonstrating more accurate risk differentiation and ranking compared to traditional assessment models. [PERSON] et al. [PERSON] et al. (2019) proposed a comprehensive airport surface operational risk assessment method, taking into account the overall operational conditions of the airport and the behavior of airport stakeholders. [PERSON] et al. [PERSON] et al. (2019) explored the key factors influencing airport risks and proposed a fuzzy hierarchical analysis model, addressing the shortcomings of the traditional analytic hierarchy process (AHP). [PERSON] et al. [PERSON] et al. (2019) proposed an airport operational situation assessment method, which selects 10 indicators as key influencing factors. By assigning weights to each level, the method allows for an evaluation of the airport's operational situation. [PERSON] et al. [PERSON] et al. (2019) evaluated the operational performance of two international airports in Taiwan through a multi-stage process, using the Analytic Network Process (ANP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess different influencing factors. In summary, there is currently limited research on risk areas with potential aircraft collision risks. Although some scholars have employed Petri nets to conduct discrete studies on aircraft operations in the complex system of the apron, few have explored its connection to collision risks. Additionally, while using indicators to assess safety provides less precision than numerical calculations, many quantitative studies remain focused on numerical assessments of collision risks without further classification or adequate visualization. This paper addresses the issue from the perspective of apron operations by establishing a Petri net model for apron operations. Based on the probability of aircraft reaching different locations within the Petri net, the corresponding collision risks are calculated. The XGBoost algorithm is then used to classify and evaluate these risks, further visualizing the results and replanning aircraft routes to reduce collision risks. This study aims to provide insights for the daily operational management of airports.