# Research on Collision Warning Method for Ship-Bridge Based on Safety Potential Field
###### Abstract
[19] proposed a method for assessing collision risk in an e-navigation environment with ship state uncertainty (i.e., stochastic behaviour) under complex manoeuvres. The proposed method can improve the understanding of bridge (IBS) situations. [PERSON]. [20] analysed the lifecycle performance and cost of bridges, and discussed ship collision prediction, optimization, and decision making in bridge areas. The AASHTO specifications and Larsen [21] have provided methods for assessing the risk of bridge collision by ships over a period of time. Recently, [PERSON] and [PERSON] have proposed a risk assessment method and ship manoeuvring simulator based on automatic identification system (AIS) data [22]. [PERSON]. [23] proposed a quantitative analysis method for ship collision risk based on AIS dynamic and static information data. This method helps to quantify ship collision risk and identify high collision risk areas. [PERSON] and [PERSON] used synergetic theory to establish a probability analysis model for ship-bridge collisions and bridge collapse [24]. Additionally, [PERSON] et al. provided a review of the relevant studies on the probability risk analysis of ship collisions [25]. These macroscopic methods typically rely on large historical databases and are useful during the established structural design phase of a bridge area. They help in implementing protective measures to prevent potential collisions and enhance the safety level of the bridge area. Micro-level studies involve qualitative and quantitative assessments of the collision risk of specific ships within the bridge channel area [4; 17]. [PERSON]. [26] studied the validation of ship collision risk using fuzzy Bayesian networks to reduce the risk of collisions in narrow waters. [PERSON]. [27] proposed a ship-bridge collision risk assessment method based on fuzzy logic, which takes into account ship characteristics, bridge parameters, and the natural environment. [PERSON]. [28] constructed a Bayesian network (BN) to analyse four aspects that affect navigation safety: environment, human factors, ships, and the natural environment. He also classified the safety levels and warning indicators for ships, reminding vessels and navigators of the navigation risks in bridge areas under different circumstances. Previous studies on ship-bridge collision prevention have typically only considered the direct relationship between bridge piers and ships, lacking research on risk management for the entire bridge area, which has certain limitations. Particularly in dynamic environments, traditional methods have failed to fully consider the uncertainties in ship trajectories and the combined effects of various environmental factors. These studies often neglect the dynamic changes of external factors such as wind and water flow, and do not comprehensively assess the navigation safety of ships in complex environments. This paper proposes a safety potential field ship and bridge warning method based on virtual force composition, which considers the effects of physical forces such as wind flow in the bridge area on ship navigation. Four types of navigational risks are defined and specified based on the safety potential field theory for static and dynamic elements in the bridge area, the channel boundary and the pilot's behaviours [29]. The wind flow in the bridge area is quantified with the Kalman filter algorithm, and its influence on the ship is reflected in the predicted ship motion state, which is then used for kinetic energy field construction. The constructed kinetic energy field is then superimposed with the safety potential field, and the total superposition field is calculated. According to the field strength range of the superposition field, a warning is carried out to judge whether there is a danger of the ship crashing into the bridge.