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Article

Fault Detection Based on Parity Equations in Multiple Lane Road Car-Following Models Using Bayesian Lane Change Estimation

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Automation and Applied Informatics Department, Politehnica University of Timisoara, Bvd. V. Parvan, No.2, 300223 Timisoara, Romania
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Management Department, Politehnica University of Timisoara, Bvd. M. Viteazu, No.1, 300223 Timisoara, Romania
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Author to whom correspondence should be addressed.
This paper is an extended version of the conference paper: Multiple Lane Road Car-Following Model using Bayesian Reasoning for Lane Change Behavior Estimation: A Smart Approach for Smart Mobility. Pop, M.-D.; Proştean, O.; Proştean, G. In Proceedings of the 3rd International Conference on Future Networks and Distributed Systems—ICFNDS ’19, Paris, France, 1–2 July 2019; ACM Press: Paris, France, 2019; pp. 1–8.
J. Sens. Actuator Netw. 2020, 9(4), 52; https://doi.org/10.3390/jsan9040052
Received: 20 August 2020 / Revised: 20 October 2020 / Accepted: 9 November 2020 / Published: 19 November 2020
(This article belongs to the Special Issue Security Threats and Countermeasures in Cyber-Physical Systems)
One of the current topics of interest in transportation science is the use of intelligent computation and IoT (Internet of Things) technologies. Researchers have proposed many approaches using these concepts, but the most widely used concept in road traffic modeling at the microscopic level is the car-following model. Knowing that the standard car-following model is single lane-oriented, the purpose of this paper is to present a fault detection analysis of the extension to a multiple lane car-following model that uses the Bayesian reasoning concept to estimate lane change behavior. After the application of the latter model on real traffic data retrieved from inductive loops placed on a road network, fault detection using parity equations was used. The standard car-following model applied separately for each lane showed the ability to perform a lane change action and to incorporate a new vehicle into the current lane. The results will highlight the advantages and the critical points of influence in the use of a multiple lane car-following model based on probabilistic estimated lane changes. Additionally, this research applied fault detection based on parity equations for the proposed model. The purpose was to deliver an overview of the faults introduced by the behavior of vehicles in adjacent lanes on the behavior of the target vehicle. View Full-Text
Keywords: Bayesian reasoning; car-following; estimation; fault detection; lane change; microscopic traffic; parity equations Bayesian reasoning; car-following; estimation; fault detection; lane change; microscopic traffic; parity equations
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MDPI and ACS Style

Pop, M.-D.; Proștean, O.; Proștean, G. Fault Detection Based on Parity Equations in Multiple Lane Road Car-Following Models Using Bayesian Lane Change Estimation. J. Sens. Actuator Netw. 2020, 9, 52. https://doi.org/10.3390/jsan9040052

AMA Style

Pop M-D, Proștean O, Proștean G. Fault Detection Based on Parity Equations in Multiple Lane Road Car-Following Models Using Bayesian Lane Change Estimation. Journal of Sensor and Actuator Networks. 2020; 9(4):52. https://doi.org/10.3390/jsan9040052

Chicago/Turabian Style

Pop, Mădălin-Dorin, Octavian Proștean, and Gabriela Proștean. 2020. "Fault Detection Based on Parity Equations in Multiple Lane Road Car-Following Models Using Bayesian Lane Change Estimation" Journal of Sensor and Actuator Networks 9, no. 4: 52. https://doi.org/10.3390/jsan9040052

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