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Adaptative Optimal Control of Nonlinear Systems Simulation to Support Hazardous Materials Traffic Management

  • Published:2021-06-22 Issue:5 Volume:32 Page:1143-1152
  • ISSN:2195-3880
  • Container-title:Journal of Control, Automation and Electrical Systems
  • language:en
  • Short-container-title:J Control Autom Electr Syst

Author:

Reis Luiz AntonioORCID,Pereira Sergio Luiz,Dias Eduardo Mario,Scoton Maria Lídia Dias

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications,Energy Engineering and Power Technology,Control and Systems Engineering

Reference31 articles.

1. Angeline, L., Choong, M. Y., Chua, B. L., Chin, R. K. Y., & Teo, K. T. K. (2019). Clustering of rippling traffic waves for driving behavioral pattern learning. In Proceedings - 2018 IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2018. https://doi.org/10.1109/IICAIET.2018.8638459

2. Das, A. K., Biswal, M. K., & Chattaraj, U. (2020). Development of a model for heterogeneous traffic simulation. In T. Mathew, G. Joshi, N. Velaga, & S. Arkatkar (Eds.), Transportation research. Singapore: Lecture Notes in Civil Engineering, Springer. https://doi.org/10.1007/978-981-32-9042-6_55

3. Di Costanzo, L., Coppola, A., Pariota, L., Petrillo, A., Santini, S., & Bifulco, G. N. (2020). Variable Speed Limits System: A Simulation-Based Case Study in the city of Naples. In Proceedings - 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2020. https://doi.org/10.1109/EEEIC/ICPSEurope49358.2020.9160560

4. Faisal, R. F., & Abdulwahhab, O. W. (2021). Design of an adaptive linear quadratic regulator for a twin rotor aerodynamic system. J Control Autom Electr Syst, 32, 404–415. https://doi.org/10.1007/s40313-020-00682-w

5. Fang, Y. L., Shi, Z. K., & Cao, J. L. (2015). Congestion phenomenon analysis, and delayed-feedback control in a modified coupled map traffic flow model containing the velocity difference. Communications in Nonlinear Science and Numerical Simulation. https://doi.org/10.1016/j.cnsns.2014.11.007

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1. Deep Q‐network learning‐based active speed management under autonomous driving environments;Computer-Aided Civil and Infrastructure Engineering;2024-06-03

2. A Smartphone-Based Solution to Manage Hazardous Materials Transportation: A Review;Proceedings of the 7th Brazilian Technology Symposium (BTSym’21);2022

3. Internet of Things Using Smartphone Sensors to Track Dangerous Goods;Proceedings of the 7th Brazilian Technology Symposium (BTSym’21);2022

4. An Improvement of CNN Model for Traffic Sign Recognition and Classification;Communications in Computer and Information Science;2022

5. Deep learning and mobile control system for hazardous materials transportation;International Journal of Intelligent Systems;2021-08-09
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