Title | ||
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Multiple Lane Road Car-Following Model using Bayesian Reasoning for Lane Change Behavior Estimation: A Smart Approach for Smart Mobility |
Abstract | ||
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Car-following modeling is one of the most used approaches for road traffic modeling. It ensures a detailed overview of vehicles behavior at microscopic traffic modeling level, taking into account some primary parameters like velocity, acceleration/deceleration, the distance between vehicles etc. A big disadvantage of this model is that is single-lane oriented, studying the current vehicle behavior based only on vehicle ahead behavior. The purpose of this paper is to deliver a new car-following model capable to adapt to multiple lanes roads, where the followed vehicle can be changed at any time. In this case, a big challenge will be the integration of a new vehicle in the established car-following model. This study attempts to estimate these different cases of lane-change based on a Bayesian reasoning estimation, facilitating the new vehicle integration on the current lane. Results will show the advantage of having a multiple lanes road traffic overview in adopting a proper traffic strategy, from the possible routes that can be reached point of view, based on lane change drivers' decisions.
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Year | DOI | Venue |
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2019 | 10.1145/3341325.3341996 | Proceedings of the 3rd International Conference on Future Networks and Distributed Systems |
Keywords | Field | DocType |
Bayesian reasoning, car-following, estimation, intelligent systems, lane change, microscopic traffic | Car following,Bayesian inference,Intelligent decision support system,Computer science,Operations research,Road traffic,Acceleration | Conference |
ISBN | Citations | PageRank |
978-1-4503-7163-6 | 0 | 0.34 |
References | Authors | |
0 | 3 |
Name | Order | Citations | PageRank |
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Mădălin-Dorin Pop | 1 | 0 | 0.34 |
Octavian Prostean | 2 | 29 | 21.20 |
Gabriela Proştean | 3 | 0 | 0.34 |