Private-MP: Privacy-Preserving Max-Pressure Control Based on Mobile Edge Computing

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

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

OriginalspracheEnglisch
Titel2025 9th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2025
Seiten1-6
ISBN (elektronisch)979-8-3315-8063-6
PublikationsstatusVeröffentlicht - 2025
Peer-Review-StatusJa

Konferenz

Titel9th International Conference on Models and Technologies for Intelligent Transportation Systems
KurztitelMT-ITS 2025
Veranstaltungsnummer9
Dauer8 - 10 September 2025
Webseite
OrtUniversity of Luxembourg
StadtLuxembourg City
LandLuxemburg

Externe IDs

ORCID /0000-0001-6555-5558/work/205334817
ORCID /0009-0007-5494-8760/work/205336536
ORCID /0000-0003-4737-5304/work/205337209

Schlagworte

Schlagwörter

  • connected vehicle, data fusion, fairness, Max-pressure control, mobile edge computing, privacy preservation