Y. Luo and L. Bölöni

Towards a more accurate agent-based multi-lane highway simulation


Cite as:

Y. Luo and L. Bölöni. Towards a more accurate agent-based multi-lane highway simulation. In Proc. of International Workshop on Agents in Traffic and Transportation (ATT10), in conjunction with the Conference on Autonomous and Multi-Agent Systems (AAMAS 2010), pp. 13–20, May 2010.

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Abstract:

The next several years will see an acceleration of the adoption of intelligent driving aid devices. Studying the impact of such devices on the overall traffic performance and safety requires highly realistic microscopic traffic simulation models, which account not only for the overall traffic flow, but also for the details and variability of the individual driver's behavior. In this paper, we first describe a series of improvements on current state of the art multilane highway driving models. The general theme of these improvements is to make the models more agent-like, by considering the specific goals and limitations of the individual drivers and vehicles. We are also performing a more detailed simulation of some of the critical steps in multi-lane highway driving, such as the process of merging at highway entrances and changing lanes. We apply our model to a real world example of the busy commuter highway 408, which crosses Orlando. Through a series of experiments, we investigate the effects of individual driver behavior on the traffic flow.

BibTeX:

@inproceedings{Luo-2010-ATT,
    author = "Y. Luo and L. B{\"o}l{\"o}ni",
    title = "Towards a more accurate agent-based multi-lane highway simulation",
    booktitle = "Proc. of International
    Workshop on Agents in Traffic and Transportation (ATT10), in conjunction
    with the Conference on Autonomous and Multi-Agent Systems
    (AAMAS 2010)",
    pages = "13-20",
    month = "May",
    year = "2010",
    abstract = {
    The next several years will see an acceleration of the adoption of
    intelligent driving aid devices. Studying the impact of such devices
    on the overall traffic performance and safety requires highly
    realistic microscopic traffic simulation models, which account not
    only for the overall traffic flow, but also for the details and
    variability of the individual driver's behavior. In this paper, we
    first describe a series of improvements on current state of the art
    multilane highway driving models. The general theme of these
    improvements is to make the models more agent-like, by considering
    the specific goals and limitations of the individual drivers and
    vehicles. We are also performing a more detailed simulation of some
    of the critical steps in multi-lane highway driving, such as the
    process of merging at highway entrances and changing lanes. We apply
    our model to a real world example of the busy commuter highway 408,
    which crosses Orlando. Through a series of experiments, we
    investigate the effects of individual driver behavior on the traffic
    flow.
    },
}

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