Private-MP: Privacy-Preserving Max-Pressure Control Based on Mobile Edge Computing
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Beitragende
Abstract
Max-pressure (MP) control has proven effective at stabilizing network queues and improving traffic throughput in large-scale urban road networks. However, conventional MP controllers based on connected vehicle (CV) data face two critical limitations: network stability diminishes when connected vehicle (CV) penetration rates are low, and significant privacy concerns arise when utilizing individual vehicle data. To address these challenges, this paper proposes a novel Private-MP controller that fuses data from both fixed-location detectors and CVs in an architecture of mobile edge computing. To fully safeguard CV privacy, including macro-route information and micro-trajectory information, Private-MP employs a privacy-preserving mechanism that combines homomorphic encryption with an adaptive randomized response strategy. Simulation studies on a network with five intersections showed that despite some increases in average vehicle delay due to privacy protection, Private-MP still ensures a more robust performance on average vehicle delay than CV-based MP in low penetration rate scenarios and outperforms traditional detector-based MP control while improving fairness among connected and non-connected vehicles.
Details
| Originalsprache | Englisch |
|---|---|
| Titel | 2025 9th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2025 |
| Seiten | 1-6 |
| ISBN (elektronisch) | 979-8-3315-8063-6 |
| Publikationsstatus | Veröffentlicht - 2025 |
| Peer-Review-Status | Ja |
Konferenz
| Titel | 9th International Conference on Models and Technologies for Intelligent Transportation Systems |
|---|---|
| Kurztitel | MT-ITS 2025 |
| Veranstaltungsnummer | 9 |
| Dauer | 8 - 10 September 2025 |
| Webseite | |
| Ort | University of Luxembourg |
| Stadt | Luxembourg City |
| Land | Luxemburg |
Externe IDs
| ORCID | /0000-0001-6555-5558/work/205334817 |
|---|---|
| ORCID | /0009-0007-5494-8760/work/205336536 |
| ORCID | /0000-0003-4737-5304/work/205337209 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- connected vehicle, data fusion, fairness, Max-pressure control, mobile edge computing, privacy preservation