scholarly journals Graphical Modeling and Simulation for a Multi-Aircraft Collision Avoidance Algorithm based on Collaborative Decisions

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 985
Author(s):  
Xi Chen ◽  
Yu Wan ◽  
Songyang Lao

The Traffic Alert and Collision Avoidance System (TCAS) is recognized worldwide as the last resort for avoiding midair collisions. The existing TCAS can solve pairwise conflict effectively, but cannot manage multi-aircraft conflict satisfactorily, and more seriously, can even trigger domino conflicts in some situation. In response to the increasingly frequent multi-aircraft conflicts, especially three-aircraft conflicts, it is necessary to improve the ability of TCAS. This paper studies the collision avoidance of multi-aircraft scenarios and innovatively proposes a collaborative optimization of a collision avoidance system (CAS) based on the state prediction of the aircraft. In the process, not only invading aircraft but also potential invading aircraft are considered in the plan for an optimal conflict resolution program. From the perspective of mathematics, the collaborative multi-aircraft conflict detection and resolution algorithm is described in detail in this paper. In the end, this paper conducts a comparative experiment to prove the feasibility of the algorithm in three-aircraft scenarios using InCAS software and Gmas simulation software based on graphical modeling of complex systems. The experimental results show that the CAS proposed in this paper can efficiently prevent the occurrence of domino conflicts and guide each aircraft to avoid conflict areas and return to their origin trajectories. In contrast, the existing TCAS will cause the target aircraft to intensify the conflict with the potential invading aircraft when avoiding intruder aircraft. The research greatly remedies the gaps in the area of multi-aircraft collision avoidance and greatly improves the ability and efficiency of TCAS.

Author(s):  
Yaseen Adnan Ahmed ◽  
Mohammed Abdul Hannan ◽  
Mahmoud Yasser Oraby ◽  
Adi Maimun

As the number of ships for marine transportation increases with the advancement of global trade, encountering multiple ships in marine traffic becomes common. This situation raises the risk of collision of the ships; hence this paper proposes a novel Fuzzy-logic based intelligent conflict detection and resolution algorithm, where the collision courses and possible avoiding actions are analyzed by considering ship motion dynamics and the input and output fuzzy membership functions are derived. As a conflict detection module, the Collision Risk (CR) is measured for each ship by using a scaled nondimensional Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) as inputs. Afterwards, the decisions for collision avoidance are made based on the calculated CR, encountering angle and relative angle of each ship measured from others. In this regard, the rules for the Fuzzy interface system are defined in accordance with the COLREGs, and the whole system is implemented on the MATLAB Simulink platform. In addition, to deal with the multiple ship encounters, the paper proposes a unique maximum-course and minimum-speed change approach for decision making, which has been found to be efficient to solve Imazu problems, and other complicated multiple-ship encounters.


2021 ◽  
Vol 9 (8) ◽  
pp. 790
Author(s):  
Yaseen Adnan Ahmed ◽  
Mohammed Abdul Hannan ◽  
Mahmoud Yasser Oraby ◽  
Adi Maimun

As the number of ships for marine transportation increases with the advancement of global trade, encountering multiple ships in marine traffic becomes common. This situation raises the risk of collision of the ships; hence, this paper proposes a novel Fuzzy-logic based intelligent conflict detection and resolution algorithm, where the collision courses and possible avoiding actions are analysed by considering ship motion dynamics and the input and output fuzzy membership functions are derived. As a conflict detection module, the Collision Risk (CR) is measured for each ship by using a scaled nondimensional Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) as inputs. Afterwards, the decisions for collision avoidance are made based on the calculated CR, encountering angle and relative angle of each ship measured from others. In this regard, the rules for the Fuzzy interface system are defined in accordance with the COLREGs, and the whole system is implemented on the MATLAB Simulink platform. In addition, to deal with the multiple ship encounters, the paper proposes a unique maximum-course and minimum-speed change approach for decision making, which has been found to be efficient to solve Imazu problems, and other complicated multiple-ship encounters.


Author(s):  
Vignesh Rajaram ◽  
Shankar C. Subramanian

In this paper, a collision avoidance algorithm (CAA) has been proposed using variable time headway considering heterogeneous traffic. The time headway used in the proposed CAA was tuned based on the traffic scenarios, the host vehicle’s load conditions and the type of the lead vehicle that the host vehicle encounters in the traffic. The proposed variable time headway would help to avoid the intervention of the collision avoidance system during normal driving and gain driver’s acceptance. The CAA was evaluated using a hardware-in-the-loop (HiL) experimental set-up integrated with the vehicle dynamic simulation software IPG/TruckMaker® for different categories of lead vehicles such as 2/3 wheelers, passenger cars, light commercial road vehicles (LCVs) and heavy commercial road vehicles (HCVs). From the results, it was observed that while following a HCV, a smaller time headway was sufficient to prevent a collision compared to following a passenger car, LCV and 2/3 wheeler.


1987 ◽  
Vol 40 (3) ◽  
pp. 283-303 ◽  
Author(s):  
R. L. Ford

The paper is mainly concerned with the principles used by TCAS (Traffic alert and Collision Avoidance System) to resolve conflicts between airborne aircraft. It leans heavily on an earlier paper which describes the threat-detection process. The simulation results given were obtained using a fast-time computer model for random traffic and comprise statistics on miss distance, warning time, etc., for a simple traffic pattern.


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