Open AccessSimulation of vehicle collisions at an unregulated intersection based on the Monte Carlo method
Author(s) -
Alexander N. Varnavsky,
A V Rogulina
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1441/1/012174
Subject(s) - collision , intersection (aeronautics) , computer science , work (physics) , advanced driver assistance systems , statistical model , monte carlo method , vehicle dynamics , simulation , set (abstract data type) , transport engineering , engineering , automotive engineering , computer security , artificial intelligence , mathematics , statistics , mechanical engineering , programming language
Currently advanced driver-assistance systems develop actively, which allow to signal to the driver about danger of collision of vehicles, necessary braking or changes of motion parameters of the car to prevent dangerous situations and accidents. The effectiveness of advanced driver-assistance systems from the parameters of their work. Therefore, the actual task is to set the optimal parameters of advanced driver-assistance systems. The values of such parameters in general can be both statistical and independent of the current road situation, and dynamic and depend on the current road situation. This problem cannot be solved without modeling dangerous situations, creating models of motion and collision risks, the results of which can be given recommendations for setting the parameters of the advanced driver-assistance systems. The aim of the work is statistical modeling collision vehicles on the unregulated crossroads and the evaluation dependency of probability collision from the parameters of the road situation. An analytical modeling of the movement of vehicles at the crossroads was used and a mathematical model of their collisions was built. With the help of statistical modeling a probability of their collision with different parameters road situation was rated. Received result can be used to configuration parameters management vehicle advanced driver-assistance systems, including dynamic.