Collision Risk Model for Encounter Situation Assessment Based on Empirical Observations

2020 ◽  
Author(s):  
Arne Lamm ◽  
Julius Moller ◽  
Axel Hahn
Keyword(s):  
Risk Model ◽  
Collision Risk ◽  
Situation Assessment

The Probability of Overlap in the Vertical Dimension

1984 ◽  
Vol 37 (1) ◽  
pp. 117-124
Author(s):  
S. Nagaoka
Keyword(s):  
Data Collection ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Risk Model ◽  
Air Traffic ◽  
Vertical Dimension ◽  
Collision Risk

The mathematical collision risk model developed by Reich can be used for evaluating the current air traffic control (ATC) separation minima. This model requires such parameters as volume of traffic, navigational errors of aircraft and the structure of routes. The navigational errors are closely related to the probability of overlap, which is one of the most important parameters for the model.Distributions of navigational errors have been studied by many researchers since the advent of the collision risk model. Because data collection on the navigational errors in the vertical dimension is expensive and time-consuming, there are few examples of observed data. Thus, at present, data on the probability of overlap in the vertical dimension are not available in a large enough sample to derive any conclusions.

A Collision Risk Model for a Crossin Track Separation Methodology

1996 ◽  
Vol 49 (3) ◽  
pp. 337-349 ◽  
Author(s):  
D. Anderson ◽  
X. G. Lin
Keyword(s):  
Risk Model ◽  
Collision Risk

The Research of Flight Collision Risk Based on Random Factors

2014 ◽  
Vol 513-517 ◽  
pp. 3964-3971
Author(s):  
Zhao Ning Zhang ◽  
Ai Ping Jia
Keyword(s):  
Differential Equation ◽  
System Performance ◽  
Nonlinear Filtering ◽  
Joint Distribution ◽  
Distribution Density ◽  
Risk Model ◽  
Collision Risk ◽  
Filtering Theory ◽  
Aircraft Flight ◽  
Gaussian Density

Using the method of stochastic differential equations to analysis two aircrafts and to establish the aircraft flight collision risk model. First the relative position and speed of the aircraft on the joint distribution density should be confirmed, and convert it into a Gaussian density to simplify the calculation of nonlinear filtering theory, and then use the method of stochastic differential equation to establish flight collision risk model, and also includes the introduction of how the CNS performance of random factors, human factors and avoidance system performance affect the flight collision. After verifying the collision risk in the example, the results show that the model is feasible.

Macroscopic collision risk model based on near miss

2021 ◽  
pp. 1-23
Author(s):  
Yangyu Zhou ◽  
Jiaxuan Yang ◽  
Xingpei Bian ◽  
Lingqi Ma ◽  
Zhen Kang
Keyword(s):  
Geographical Distribution ◽  
Risk Model ◽  
Grid Method ◽  
Near Miss ◽  
Distribution Characteristics ◽  
Data Sampling ◽  
Collision Risk ◽  
Model Based ◽  
Marine Traffic ◽  
The Subject

Abstract Using near miss data detected from non-accident information to analyse marine traffic risk can alleviate some of the limitations of accident-based methods. A model based on an arena for detecting scenes of near miss is proposed to detect comprehensively those ship encounters with potential collision risk. To eliminate the influence of data sampling frequency on the detection of scenes of near miss, a single near miss is defined as the whole progress of traffic state from the time the target ship sails into the arena of the subject ship to the time it leaves the arena of the subject ship. To research the geographical distribution characteristics of marine traffic risk, first, a statistical model for the scenes of near miss based on the water grid method is proposed, and then a macroscopic collision risk model based on near miss is developed. The geographical distribution characteristics of marine traffic risk in the Bohai Sea are analysed, and the water areas of high marine traffic risk are obtained. The findings can provide theoretical support for marine safety management.

scholarly journals On the Longitudinal Collision Risk Model Taking into Account the Mach Number Assignments

1996 ◽  
Vol 95 (0) ◽  
pp. 109-116
Author(s):  
Sakae NAGAOKA ◽  
Midori TAKAHASHI ◽  
Osamu AMAI
Keyword(s):  
Mach Number ◽  
Risk Model ◽  
Collision Risk

A Unified Collision Risk Model for Unmanned Aircraft Systems

2021 ◽  
Author(s):  
Suraj Bijjahalli ◽  
Alessandro Gardi ◽  
Nichakorn Pongsakornsathien ◽  
Roberto Sabatini
Keyword(s):  
Risk Model ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Collision Risk ◽  
Aircraft Systems

Study on Free Flight Collision Risk Based on the Error Distribution of Three-Dimensional Position

2014 ◽  
Vol 1030-1032 ◽  
pp. 2245-2253
Author(s):  
Zhao Ning Zhang ◽  
Yu Wen Liang ◽  
Xing Wu Cao
Keyword(s):  
Risk Model ◽  
Three Dimensional ◽  
Error Distribution ◽  
Position Error ◽  
Collision Risk ◽  
Free Flight ◽  
Initial State ◽  
Actual Position ◽  
Normal Probability ◽  
Error Ellipsoid

This paper is aimed to evaluate the collision risk in free flight. The collision risk between aircrafts is mostly closely relates to position error, due to which the actual position of the aircraft is different from the displaying position and the former is in the vicinity of the latter. Analyzing error factors closely associated with the risk of collision, such as position error caused by CNS performance, altimeters and CDTI system, and according to the error distribution, the region of actual position of aircraft can be considered as a three-dimensional joint normal probability density ellipsoid. The two adjacent planes can be abstracted into two particles, of which one is based to determine position error ellipsoid, and the other is based to establish collision slab. A free flight collision risk model is established, then simplified by linear transformation according to the principle of relative motion. Using Monte Carlo method of mean of uniform random numbers, given initial state, the collision risk in free flight can be obtained. Numerical results demonstrate the feasibility of this model.

Feasibility Study on Independent Instrument Approach Operations between Runways 36L/18R and 01/19 at Beijing Capital International Airport

2020 ◽  
Vol 2674 (11) ◽  
pp. 741-755
Author(s):  
Lili Wang ◽  
Shengnan Lu ◽  
Fang Wei
Keyword(s):  
North China ◽  
Risk Model ◽  
Reaction Times ◽  
Position Error ◽  
Theoretical Research ◽  
Civil Aviation ◽  
Trajectory Data ◽  
Collision Risk ◽  
International Airport ◽  
The North

Beijing Capital International Airport is one of the busiest hub airports in the world, but its capacity is limited. Reducing the minimum radar interval during instrument approaches would be feasible to increase capacity. The airport has three parallel runways; the distance between runways 36L/18R and 01/19 is 3.485 km. Currently, because there is no final monitoring seat, the dependent parallel instrument approach mode is adopted on the two runways; approaching aircraft must maintain a 4 km safety separation. This paper focuses on whether the 4 km radar safety separation for parallel instrument approaches could be reduced to 3.485 km without the final monitoring. This would mean implementing independent instrument approach operations between the two runways. To consider this, a new collision risk model based on position error probability and aircraft kinematics is proposed. A test program to acquire data on controllers’ reaction times in abnormal situations was designed and implemented over 10 days by the North China Air Traffic Management Bureau (ATMB). Furthermore, six months of radar trajectory data was collected at the airport. This was analyzed and processed to obtain the position error, speed, and other parameters required for the calculation of the collision risk model. The results show that the independent instrument approach operations between runways 36L/18R and 01/19 would be feasible the within safety target level set by the International Civil Aviation Organization (ICO). Based on the theoretical research results, the North China ATCB implemented independent instrument approaches between runways 36L/18R and 01/19 on December 25, 2018; it has operated safely since.

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