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Multiple Lane Road Car-Following Model using Bayesian Reasoning for Lane Change Behavior Estimation: A Smart Approach for Smart Mobility

Authors:

Mădălin-Dorin Pop,

Octavian Proştean,

Gabriela ProşteanAuthors Info & Claims

ICFNDS '19: Proceedings of the 3rd International Conference on Future Networks and Distributed Systems

Article No.: 6, Pages 1 - 8

https://doi.org/10.1145/3341325.3341996

Published: 01 July 2019 Publication History

Abstract

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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Cited By

Pop MProstean OMicea M(2022)Evaluation of the Use of an Intelligent System in the Calibration of a Refined Car-Following Model2022 IEEE 22nd International Symposium on Computational Intelligence and Informatics and 8th IEEE International Conference on Recent Achievements in Mechatronics, Automation, Computer Science and Robotics (CINTI-MACRo)10.1109/CINTI-MACRo57952.2022.10029500(000107-000112)Online publication date: 21-Nov-2022
https://doi.org/10.1109/CINTI-MACRo57952.2022.10029500
Joubari OOthman JVèque V(2022)Markov Chain Mobility Model for Multi-lane HighwaysMobile Networks and Applications10.1007/s11036-021-01893-427:3(1286-1298)Online publication date: 21-Feb-2022
https://doi.org/10.1007/s11036-021-01893-4
Oumaima EJalel BVéronique V(2021)A Stochastic Traffic Model for Congestion Detection in Multi-lane HighwaysAd Hoc Networks10.1007/978-3-030-67369-7_7(87-99)Online publication date: 31-Jan-2021
https://doi.org/10.1007/978-3-030-67369-7_7
Show More Cited By

Index Terms

Multiple Lane Road Car-Following Model using Bayesian Reasoning for Lane Change Behavior Estimation: A Smart Approach for Smart Mobility

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cover image ACM Other conferences

ICFNDS '19: Proceedings of the 3rd International Conference on Future Networks and Distributed Systems

July 2019

346 pages

ISBN:9781450371636

DOI:10.1145/3341325

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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CNAM: Conservatoire des Arts et Métiers

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Publication History

Published: 01 July 2019

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ICFNDS '19

ICFNDS '19: 3rd International Conference on Future Networks and Distributed Systems

July 1 - 2, 2019

Paris, France

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Cited By

Pop MProstean OMicea M(2022)Evaluation of the Use of an Intelligent System in the Calibration of a Refined Car-Following Model2022 IEEE 22nd International Symposium on Computational Intelligence and Informatics and 8th IEEE International Conference on Recent Achievements in Mechatronics, Automation, Computer Science and Robotics (CINTI-MACRo)10.1109/CINTI-MACRo57952.2022.10029500(000107-000112)Online publication date: 21-Nov-2022
https://doi.org/10.1109/CINTI-MACRo57952.2022.10029500
Joubari OOthman JVèque V(2022)Markov Chain Mobility Model for Multi-lane HighwaysMobile Networks and Applications10.1007/s11036-021-01893-427:3(1286-1298)Online publication date: 21-Feb-2022
https://doi.org/10.1007/s11036-021-01893-4
Oumaima EJalel BVéronique V(2021)A Stochastic Traffic Model for Congestion Detection in Multi-lane HighwaysAd Hoc Networks10.1007/978-3-030-67369-7_7(87-99)Online publication date: 31-Jan-2021
https://doi.org/10.1007/978-3-030-67369-7_7
Pop MProștean ODavid TProștean G(2020)Hybrid Solution Combining Kalman Filtering with Takagi–Sugeno Fuzzy Inference System for Online Car-Following Model CalibrationSensors10.3390/s2019553920:19(5539)Online publication date: 27-Sep-2020
https://doi.org/10.3390/s20195539
Pop MProștean OProștean G(2020)Fault Detection Based on Parity Equations in Multiple Lane Road Car-Following Models Using Bayesian Lane Change EstimationJournal of Sensor and Actuator Networks10.3390/jsan90400529:4(52)Online publication date: 19-Nov-2020
https://doi.org/10.3390/jsan9040052
Oumaima EJalel BVeronique V(2020)Continuous Time Markov Chain Traffic Model for Urban EnvironmentsGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9348256(1-6)Online publication date: Dec-2020
https://doi.org/10.1109/GLOBECOM42002.2020.9348256

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