# A Fuzzy Path Selection Strategy for Aircraft Landing on a Carrier
## 1 Introduction  
Aircraft landing on a carrier is a task with high risk [1]. An aircraft can land on a carrier successfully with a probability of 70%, and the rate is lower at night. In comparison with land-based aircraft, landing on an aircraft carrier is more dangerous and complicated since a series of particular conditions needs to be taken into account. In addition, the flight condition and the maritime environment are changing all the time, and these uncertainties make the landing task difficult [2, 3]. In order to guide the aircraft landing safely, an aircraft carrier must be equipped with certain special guidance devices such as a Fresnel lens optical landing system [4], an all-weather radar landing system [5] and so on. Further, a variety of commanders and staff are needed to guarantee the landing safety of aircraft and cope with all emergencies [6]. Among them, the landing console operator (LCO) onboard is responsible for supervising the aircraft, which is about 20 nautical miles away from the aircraft carrier. The landing signal officer (LSO) concentrates on the last step of landing and he/sheassists the pilot to land safely using body language or by talking to the pilot directly [7]. The air officer in the control tower does the work related to the flight deck, e.g., preparing the flight deck for launching, managing the aircraft on the flight deck and emptying the flight deck for landing. Each staff member mentioned above assumes their own duty at different stages of landing, and the safe landing of aircraft is accomplished by their team work. In each landing stage, the above commanders and staff make a decision to guide the aircraft in a very short time based on their knowledge and the information shown on various instruments, which makes high-level demands on their judgment and reaction [8]. However, there is fuzziness in the environment and flight information, and accurate judgment cannot always be reached quickly, which is attributed to the complicacy and variability of weather at sea, the lack of comprehensive information and other subjective factors. In recent years, artificial intelligence (AI) has been widely applied to various fields, and many great achievements have been made in this field. For instance, the complex changes and uncertainties in manufacturing can be managed by AI and machine learning techniques [9]. Another case in point is the routing problems for ground vehicles, and minimal total cost can be achieved using AI without violating the capacity and time window constraints [10]. As the AI-based methods have shown better performance than humans in ranking the candidates [11] and optimizing the index [12], these methods are expected to be introduced into the decision-making system of the aircraft carrier to reduce the workload of the staff onboard and to improve the safety level of the landing. Currently, the studies on the landing of aircraft concentrate primarily on the last step, i.e., the design of an automatic landing controller and the interaction between the pilot and the LSO. For example, the landing safety is analyzed based on rough set theory, and the values of kinematic parameters and their combinations are determined to define the boundary conditions for safe landing [13]. The action of the LSO is described by a fuzzy language, and multiple AI techniques are applied to the landing decision-support tool. The obtained landing decision-support tool allows the LSO to make better time-critical decisions in a dangerous environment [14]. The gesture of the LSO is also studied extensively, and a multi-signal gesture database, which requires both body knowledge and hand knowledge of the LSO to distinguish gestures, was introduced. Subsequently, the true meaning of gestures obtained based on the gesture database is communicated to the pilot to enable a better understanding and to assist landing [15]. Our team also conducted intensive research on the automatic landing guidance technology.