Bi-level Optimization

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Publications

  • 2020
    Anouer Bennajeh, Lamjed Ben Said

    Multi-agent cooperation for an active perception based on driving behavior: Application in a car-following behavior

    This paper introduces a five-layer driving model emphasizing perception through visual processing, comprehension, and projection within car-following behavior. Simulation results, using both urban conditions and the NGSIM dataset., 2020

    Résumé

    Perception is presented as a predominant concern in the functioning of a driving system, where it is necessary to understand how the information, events, and actions of each influence the state of the environment and the objectives of the driver, immediately and in the near future. In this context, we present in this paper a driving model composed of five layers which ensure the autonomy and road safety of a driver agent, in particular, we are interested in this article in the concept of perception which is translated by the first three layers of our driving model, which are: visual perception, comprehension and projection, where the execution of these three layers is based on the driving behavior adopted by the driver agent, which is in our case the car-following driving behavior. Furthermore, we present in this paper two simulation scenarios, the first one is realized based on urban area conditions, and the second one is conducted by using Next Generation SIMulation (NGSIM) dataset of a highway in Los Angeles, California. In this context, the experimental results present the effectiveness of our driving model based on the imitation of human behavior and according to reducing the duration of perception.

  • 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

    https://chatgpt.com/c/68d6582b-d000-8326-8778-077d05d845e8, 2019

    Résumé

    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.