Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior
Road crashes are present as an epidemic in road traffic and continue to grow up, where, according to World Health Organization; they cause more than 1.24 million deaths each year and 20 to 50 million non-fatal injuries, so they should represent by 2020 the third leading global cause of illness and i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2019-11-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2019.1673018 |
| _version_ | 1827817580917686272 |
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| author | Anouer Bennajeh Slim Bechikh Lamjed Ben Said Samir Aknine |
| author_facet | Anouer Bennajeh Slim Bechikh Lamjed Ben Said Samir Aknine |
| author_sort | Anouer Bennajeh |
| collection | DOAJ |
| description | Road crashes are present as an epidemic in road traffic and continue to grow up, where, according to World Health Organization; they cause more than 1.24 million deaths each year and 20 to 50 million non-fatal injuries, so they should represent by 2020 the third leading global cause of illness and injury. In this context, we are interested in this paper to the car-following driving behavior problem, since it alone accounts for almost 70% of road accidents, which they are caused by the incorrect judgment of the driver to keep a safe distance. Thus, we propose in this paper a decision-making model based on bi-level modeling, whose objective is to ensure the integration between road safety and the reducing travel time. To ensure this objective, we used the fuzzy logic approach to model the anticipation concept in order to extract more unobservable data from the road environment. Furthermore, we used the fuzzy logic approach in order to model the driver behaviors, in particular, the normative behaviors. The experimental results indicate that the decision to increase in velocity based on our model is ensured in the context of respecting the road safety. |
| first_indexed | 2024-03-12T00:36:16Z |
| format | Article |
| id | doaj.art-8ab6bf3d052e4bbaa8e6f32a36b88547 |
| institution | Directory Open Access Journal |
| issn | 0883-9514 1087-6545 |
| language | English |
| last_indexed | 2024-03-12T00:36:16Z |
| publishDate | 2019-11-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Artificial Intelligence |
| spelling | doaj.art-8ab6bf3d052e4bbaa8e6f32a36b885472023-09-15T09:33:57ZengTaylor & Francis GroupApplied Artificial Intelligence0883-95141087-65452019-11-0133131157117810.1080/08839514.2019.16730181673018Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving BehaviorAnouer Bennajeh0Slim Bechikh1Lamjed Ben Said2Samir Aknine3Université de TunisUniversité de TunisUniversité de TunisUniversité Claude Bernard Lyon 1 UCBLRoad crashes are present as an epidemic in road traffic and continue to grow up, where, according to World Health Organization; they cause more than 1.24 million deaths each year and 20 to 50 million non-fatal injuries, so they should represent by 2020 the third leading global cause of illness and injury. In this context, we are interested in this paper to the car-following driving behavior problem, since it alone accounts for almost 70% of road accidents, which they are caused by the incorrect judgment of the driver to keep a safe distance. Thus, we propose in this paper a decision-making model based on bi-level modeling, whose objective is to ensure the integration between road safety and the reducing travel time. To ensure this objective, we used the fuzzy logic approach to model the anticipation concept in order to extract more unobservable data from the road environment. Furthermore, we used the fuzzy logic approach in order to model the driver behaviors, in particular, the normative behaviors. The experimental results indicate that the decision to increase in velocity based on our model is ensured in the context of respecting the road safety.http://dx.doi.org/10.1080/08839514.2019.1673018 |
| spellingShingle | Anouer Bennajeh Slim Bechikh Lamjed Ben Said Samir Aknine Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior Applied Artificial Intelligence |
| title | Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior |
| title_full | Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior |
| title_fullStr | Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior |
| title_full_unstemmed | Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior |
| title_short | Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior |
| title_sort | bi level decision making modeling for an autonomous driver agent application in the car following driving behavior |
| url | http://dx.doi.org/10.1080/08839514.2019.1673018 |
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