Navigation Systems May Deteriorate Stability in Traffic Networks
Advanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics originating from the widespread adoption of these technologi...
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| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Control Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10520878/ |
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| author | Gianluca Bianchin Fabio Pasqualetti |
| author_facet | Gianluca Bianchin Fabio Pasqualetti |
| author_sort | Gianluca Bianchin |
| collection | DOAJ |
| description | Advanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics originating from the widespread adoption of these technologies have remained largely unexplored until now. In this paper, we propose a dynamic model where drivers imitate the path preferences of previous drivers, and we study the properties of its equilibrium points. Our model is a dynamic generalization of the classical <italic>traffic assignment framework</italic>, and extends it by accounting for dynamics both in the path decision process and in the network's traffic flows. We show that, when travelers learn shortest paths by imitating other travelers, the overall traffic system benefits from this mechanism and transfers the maximum admissible amount of traffic demand. On the other hand, we demonstrate that, when the travel delay functions are not sufficiently steep or the rates at which drivers imitate previous travelers are not adequately chosen, the trajectories of the traffic system may fail to converge to an equilibrium point, thus compromising asymptotic stability. Illustrative numerical simulations combined with empirical data from highway sensors illustrate our findings. |
| format | Article |
| id | doaj-art-6624b85b7fdc444d9136b15d093f18af |
| institution | DOAJ |
| issn | 2694-085X |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Control Systems |
| spelling | doaj-art-6624b85b7fdc444d9136b15d093f18af2025-08-20T02:44:28ZengIEEEIEEE Open Journal of Control Systems2694-085X2024-01-01323925210.1109/OJCSYS.2024.339727010520878Navigation Systems May Deteriorate Stability in Traffic NetworksGianluca Bianchin0https://orcid.org/0000-0002-3234-5535Fabio Pasqualetti1https://orcid.org/0000-0002-8457-8656ICTEAM Institute and the Department of Mathematical Engineering, Université catholique de Louvain, Ottignies-Louvain-la-Neuve, BelgiumDepartment of Mechanical Engineering, The University of California Riverside, Riverside, CA, USAAdvanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics originating from the widespread adoption of these technologies have remained largely unexplored until now. In this paper, we propose a dynamic model where drivers imitate the path preferences of previous drivers, and we study the properties of its equilibrium points. Our model is a dynamic generalization of the classical <italic>traffic assignment framework</italic>, and extends it by accounting for dynamics both in the path decision process and in the network's traffic flows. We show that, when travelers learn shortest paths by imitating other travelers, the overall traffic system benefits from this mechanism and transfers the maximum admissible amount of traffic demand. On the other hand, we demonstrate that, when the travel delay functions are not sufficiently steep or the rates at which drivers imitate previous travelers are not adequately chosen, the trajectories of the traffic system may fail to converge to an equilibrium point, thus compromising asymptotic stability. Illustrative numerical simulations combined with empirical data from highway sensors illustrate our findings.https://ieeexplore.ieee.org/document/10520878/Dynamical flow networksnetwork controltraffic networks |
| spellingShingle | Gianluca Bianchin Fabio Pasqualetti Navigation Systems May Deteriorate Stability in Traffic Networks IEEE Open Journal of Control Systems Dynamical flow networks network control traffic networks |
| title | Navigation Systems May Deteriorate Stability in Traffic Networks |
| title_full | Navigation Systems May Deteriorate Stability in Traffic Networks |
| title_fullStr | Navigation Systems May Deteriorate Stability in Traffic Networks |
| title_full_unstemmed | Navigation Systems May Deteriorate Stability in Traffic Networks |
| title_short | Navigation Systems May Deteriorate Stability in Traffic Networks |
| title_sort | navigation systems may deteriorate stability in traffic networks |
| topic | Dynamical flow networks network control traffic networks |
| url | https://ieeexplore.ieee.org/document/10520878/ |
| work_keys_str_mv | AT gianlucabianchin navigationsystemsmaydeterioratestabilityintrafficnetworks AT fabiopasqualetti navigationsystemsmaydeterioratestabilityintrafficnetworks |