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An Integrated Turning Movements Estimation to Petri Net Based Road Traffic Modeling

AMIPS Research Team, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat 10000, Morocco
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J. Sens. Actuator Netw. 2019, 8(3), 49; https://doi.org/10.3390/jsan8030049
Received: 9 August 2019 / Revised: 13 September 2019 / Accepted: 15 September 2019 / Published: 18 September 2019
(This article belongs to the Special Issue Wireless Technologies Applied to Connected and Automated Vehicles)
The tremendous increase in the urban population highlights the need for more efficient transport systems and techniques to alleviate the increasing number of the resulting traffic-associated problems. Modeling and predicting road traffic flow are a critical part of intelligent transport systems (ITSs). Therefore, their accuracy and efficiency have a direct impact on the overall functioning. In this scope, a new approach for predicting the road traffic flow is proposed that combines the Petri nets model with a dynamic estimation of intersection turning movement counts to ensure a more accurate assessment of its performance. Thus, this manuscript extends our work by introducing a new feature, namely turning movement counts, to attain a better prediction of road traffic flow. A simulation study is conducted to get a better understanding of how predictive models perform in the context of estimating turning movements. View Full-Text
Keywords: turning; predictive models; neural networks; random forest; linear regression; intersection; transportation; data models; batch; Petri nets; traffic turning; predictive models; neural networks; random forest; linear regression; intersection; transportation; data models; batch; Petri nets; traffic
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Riouali, Y.; Benhlima, L.; Bah, S. An Integrated Turning Movements Estimation to Petri Net Based Road Traffic Modeling. J. Sens. Actuator Netw. 2019, 8, 49.

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