Developing a parameterized simulation platform with intelligent synthetic agents for training driver candidates
Author(s) -
Abdullah Çavuşoğlu,
İsmail Kurnaz
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2010.12.120
Subject(s) - computer science , simulation , training (meteorology) , driving simulator , parameterized complexity , intelligent transportation system , real time computing , graph , parametric statistics , interface (matter) , transport engineering , operating system , algorithm , statistics , physics , mathematics , bubble , theoretical computer science , maximum bubble pressure method , meteorology , engineering
This study presents a driver Traffic Training Simulator (TTS) that utilizes intelligent synthetic actors. The movements of intelligent actors are realized using a network flow graph consisting of segment nodes. The intelligent actors in traffic are capable of such objectives as vehicles and lane following. In addition, they are capable of moving according to the traffic signs and lights. The duration of traffic lights can parametrically be determined by the simulator interface. Moreover, parametric values such as weather conditions, seasons, and sunlight can be fed to the simulator as inputs. Similarly, the type of the driver’s vehicle and other intelligent vehicles and their numbers can also be parametrically determined. The driver is able to drive in the heavy and light traffic conditions. Currently we are focusing on incorporating the hardware components into the system. Following the tests for the candidates with the system is expected to take place in driver training schools
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