Using fuzzy logic to control vehicles velocity in traffic system
Approaching the desired vehicle speed by using a FUZZY logic controller is the goal of this article. It provides a controller that both increases and decreases in velocity). The lead vehicle and the follow vehicle have the same input variables, such as velocity or velocity error, acceleration factor...
| Main Authors: | , |
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| Format: | Conference Paper |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/43535 |
| _version_ | 1848756723325599744 |
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| author | Alghamdi, A. Eren, Halit |
| author_facet | Alghamdi, A. Eren, Halit |
| author_sort | Alghamdi, A. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Approaching the desired vehicle speed by using a FUZZY logic controller is the goal of this article. It provides a controller that both increases and decreases in velocity). The lead vehicle and the follow vehicle have the same input variables, such as velocity or velocity error, acceleration factor, reaction factor (a), and deceleration factor (ß), while the bumper-to-bumper gap (Xrel) is not important for the lead vehicle. The relation between inputs and output is discussed. This paper explains a novel approach to the simulation of a congestion system by using a closed-loop system for 69 vehicles. This work will continue to solve the congestion problem. |
| first_indexed | 2025-11-14T09:16:44Z |
| format | Conference Paper |
| id | curtin-20.500.11937-43535 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:16:44Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-435352017-09-13T14:01:55Z Using fuzzy logic to control vehicles velocity in traffic system Alghamdi, A. Eren, Halit Approaching the desired vehicle speed by using a FUZZY logic controller is the goal of this article. It provides a controller that both increases and decreases in velocity). The lead vehicle and the follow vehicle have the same input variables, such as velocity or velocity error, acceleration factor, reaction factor (a), and deceleration factor (ß), while the bumper-to-bumper gap (Xrel) is not important for the lead vehicle. The relation between inputs and output is discussed. This paper explains a novel approach to the simulation of a congestion system by using a closed-loop system for 69 vehicles. This work will continue to solve the congestion problem. 2013 Conference Paper http://hdl.handle.net/20.500.11937/43535 10.3182/20130626-3-AU-2035.00033 restricted |
| spellingShingle | Alghamdi, A. Eren, Halit Using fuzzy logic to control vehicles velocity in traffic system |
| title | Using fuzzy logic to control vehicles velocity in traffic system |
| title_full | Using fuzzy logic to control vehicles velocity in traffic system |
| title_fullStr | Using fuzzy logic to control vehicles velocity in traffic system |
| title_full_unstemmed | Using fuzzy logic to control vehicles velocity in traffic system |
| title_short | Using fuzzy logic to control vehicles velocity in traffic system |
| title_sort | using fuzzy logic to control vehicles velocity in traffic system |
| url | http://hdl.handle.net/20.500.11937/43535 |