Probabilistic model checking of the next-generation airborne collision avoidance system

2016 ◽  
Author(s):  
Ryan W. Gardner ◽  
Daniel Genin ◽  
Raymond McDowell ◽  
Christopher Rouff ◽  
Anshu Saksena ◽  
...  
Keyword(s):  
Model Checking ◽  
Collision Avoidance ◽  
Probabilistic Model ◽  
Probabilistic Model Checking ◽  
Next Generation ◽  
Collision Avoidance System

UAS Pilot Assessments of Display and Alerting for the Airborne Collision Avoidance System XU

2020 ◽  
Vol 64 (1) ◽  
pp. 159-163
Author(s):  
Casey L. Smith ◽  
R. Conrad Rorie ◽  
Kevin J. Monk ◽  
Jillian Keeler ◽  
Garrett G. Sadler
Keyword(s):  
Collision Avoidance ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Next Generation ◽  
National Airspace System ◽  
Aircraft Systems ◽  
Collision Avoidance System ◽  
Further Development ◽  
Initial Iteration ◽  
Integrated Display

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback of these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS XU alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

scholarly journals Probabilistic Model Checking and Non-standard Multi-objective Reasoning

2014 ◽  
pp. 1-16 ◽  
Author(s):  
Christel Baier ◽  
Clemens Dubslaff ◽  
Sascha Klüppelholz ◽  
Marcus Daum ◽  
Joachim Klein ◽  
...  
Keyword(s):  
Model Checking ◽  
Probabilistic Model ◽  
Probabilistic Model Checking ◽  
Multi Objective ◽  
Objective Reasoning

scholarly journals A Railway Scheduling Method using Probabilistic Model Checking

2019 ◽  
Vol 9 (1) ◽  
pp. 6694-6698
Keyword(s):  
Model Checking ◽  
Probabilistic Model ◽  
Probabilistic Model Checking ◽  
Railway Transportation ◽  
Railway Network ◽  
Double Line ◽  
Arrival Times ◽  
Scheduling Method ◽  
Prism Model ◽  
The Impact

Trains scheduling is an important problem in railway transportation. Many companies use fixed train timetabling to handle this problem. Train delays can affect the pre-defined timetables and postpone destination arrival times. Besides, delay propagation may affect other trains and degrade the performance of a railway network. An optimal timetable minimizes the total propagated delays in a network. In this paper, we propose a new approach to compute the expected propagated delays in a railway network. As the main contribution of the work, we use Discrete-time Markov chains to model a railway network with a fixed timetable and use probabilistic model checking to approximate the expected delays and the probability of reaching destinations with a desired delay. We use PRISM model checker to apply our approach for analyzing the impact of different train scheduling in double line tracks.

Evaluating probabilistic model checking tools for verification of robot control policies

2016 ◽  
Vol 29 (2) ◽  
pp. 287-299 ◽  
Author(s):  
Shashank Pathak ◽  
Luca Pulina ◽  
Armando Tacchella
Keyword(s):  
Model Checking ◽  
Probabilistic Model ◽  
Robot Control ◽  
Probabilistic Model Checking ◽  
Control Policies
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