Estimation of Human s Performance in Automobile Driving
Year
: 2009
Abstract: The combination of increasing population,growing demand for mobility, and limited funds
and real estate for building new roads places a strain on the current transportation infrastructure. It
seems that the vehicle control scheme should be changed. In order to this, it is necessary to design a
machine or intelligent system that can cooperate with human in automobile driving. The roll of the
machine depends on the human s behaviour. If human drives correctly, the machine command should
not be effective, but, if he couldn t drive carefully for any reason, the roll of the machine would be
more effective. Therefore, at first it should define a function that express the human s behavior within
automobile driving. The goal of this paper is introducing a method which can estimate the human s
performance within automobile driving. These data determine the level of human and machine
autonomy. Fuzzy logic is used for human s behaviour simulation and for vehicle modelling, the single
track bicycle model is used
and real estate for building new roads places a strain on the current transportation infrastructure. It
seems that the vehicle control scheme should be changed. In order to this, it is necessary to design a
machine or intelligent system that can cooperate with human in automobile driving. The roll of the
machine depends on the human s behaviour. If human drives correctly, the machine command should
not be effective, but, if he couldn t drive carefully for any reason, the roll of the machine would be
more effective. Therefore, at first it should define a function that express the human s behavior within
automobile driving. The goal of this paper is introducing a method which can estimate the human s
performance within automobile driving. These data determine the level of human and machine
autonomy. Fuzzy logic is used for human s behaviour simulation and for vehicle modelling, the single
track bicycle model is used
Keyword(s): Fuzzy control,Shared control of human and machine,Genetic algorithm
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Estimation of Human s Performance in Automobile Driving
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| contributor author | عباس ولی زاده | en |
| contributor author | محمدرضا اکبرزاده توتونچی | en |
| contributor author | Mohammad Reza Akbarzadeh Totonchi | fa |
| date accessioned | 2020-06-06T13:57:51Z | |
| date available | 2020-06-06T13:57:51Z | |
| date copyright | 7/15/2009 | |
| date issued | 2009 | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/3376644 | |
| description abstract | The combination of increasing population,growing demand for mobility, and limited funds and real estate for building new roads places a strain on the current transportation infrastructure. It seems that the vehicle control scheme should be changed. In order to this, it is necessary to design a machine or intelligent system that can cooperate with human in automobile driving. The roll of the machine depends on the human s behaviour. If human drives correctly, the machine command should not be effective, but, if he couldn t drive carefully for any reason, the roll of the machine would be more effective. Therefore, at first it should define a function that express the human s behavior within automobile driving. The goal of this paper is introducing a method which can estimate the human s performance within automobile driving. These data determine the level of human and machine autonomy. Fuzzy logic is used for human s behaviour simulation and for vehicle modelling, the single track bicycle model is used | en |
| language | English | |
| title | Estimation of Human s Performance in Automobile Driving | en |
| type | Conference Paper | |
| contenttype | External Fulltext | |
| subject keywords | Fuzzy control | en |
| subject keywords | Shared control of human and machine | en |
| subject keywords | Genetic algorithm | en |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1016190.html | |
| conference title | 3rd joint congress on fuzzy and intelligent systems | en |
| conference location | یزد | fa |
| identifier articleid | 1016190 |