How Road and Mobile Networks Correlate: Estimating Urban Traffic Using Handovers

Derrmann, Thierry; Frank, Raphaël; Viti, Francesco; Engel, Thomas

doi:10.1109/tits.2019.2901373

Cited by 6 publications

(4 citation statements)

References 31 publications

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“…Ur Rehman et al in [11] modeled downlink throughput in the LTE network based on several independent variables related to the conditions of radio networks (traffic) using multilayer neural networks. The paper [12] presents the connection between road traffic and mobile networks in urban areas through predictive models of traffic flows, which were created based on mobile network signal data. In [13], the authors presented several machine learning and deep learning models for throughput prediction, which is crucial for delay reduction in online streaming services.…”

Section: Scientific Background Of the Researchmentioning

confidence: 99%

Prediction of User Throughput in the Mobile Network Along the Motorway and Trunk Road

Ćurguz¹,

Banjanin²,

Stojčić³

2022

Sci. Eng. Technol.

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The main goal of this research is to create a machine learning model for predicting user throughput in the mobile 4G network of the network provider M:tel Banja Luka, Bosnia and Herzegovina. The geographical area of the research is limited to the section of Motorway "9th January" (M9J) Banja Luka - Doboj, between the node Johovac and the town of Prnjavor (P-J section), and the area of the section of trunk road M17, between the node Johovac and the town of Doboj (J-D section). Based on the set of collected data, several models based on machine learning techniques were trained and tested together with the application of the Correlation-based Feature Selection (CFS) method to reduce the space of input variables. The test results showed that the models based on k-Nearest Neighbors (k-NN) have the lowest relative prediction error, for both sections, while the model created for the trunk road section has significantly better performance.

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Section: Scientific Background Of the Researchmentioning

confidence: 99%

Prediction of User Throughput in the Mobile Network Along the Motorway and Trunk Road

Ćurguz¹,

Banjanin²,

Stojčić³

2022

Sci. Eng. Technol.

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“…Cellular systems [40] have also been used to provide alternative methods to the cost and coverage limitations associated with infrastructure-based solutions, and some works have been proposed to estimate volumes of vehicles from anonymous cellular phone call data [41], [42]. These systems cannot generally provide fine-grained traffic volume estimates and require long processing time which make them unsuitable for real-time estimation [15], [43].…”

Section: State-of-the-art and Proposed Framework A Review Of Ubimentioning

confidence: 99%

Toward a Cost-Effective Motorway Traffic State Estimation From Sparse Speed and GPS Data

et al. 2021

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In this paper, we propose a new data-driven traffic state estimation model that estimates traffic flow based on average speed data only. The model is devised to implement a cost-effective framework that aggregates heterogeneous sources of vehicles' GPS and speed measurements to infer traffic flow using a novel triplet system called Conditionally Gaussian Observed Markov Fuzzy Switching Systems (CGOMFSM). Unlike its hard counterpart, CGOMFSM allows for a transient and gradual representation of traffic state transition and hence improves the estimation performance using a tractable scheme. The potential of the proposed model is illustrated through an application to the problem of traffic incident detection, particularly sporadic traffic congestion caused by unexpected road conditions. The performance of the proposed model is assessed using real traffic datasets from England highways. A simulation of traffic in the city of Salalah in Oman was conducted to evaluate the efficacy of the CGOMFSM-based traffic estimation and incident detection schemes with different penetration rates.

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“…Starting from the observations made in [14], we investigated the use of administrative boundaries as a partitioning method to compute the MFD. In that paper, the authors propose a model to link mobile network signaling data to the state of the underlying transportation infrastructure.…”

Section: Approachmentioning

confidence: 99%

“…For this reason, we propose to use the existent administrative boundaries of a city to use them to partition the area and compute the MFDs. This choice is also motivated by a recent study [14], where the authors observed a possible correlation between the clusters generated with state-ofthe-art methods for MFD analysis, and the administrative neighborhoods in the City of Luxembourg, while comparing the traffic patterns arising from the mobility modelled by the Luxembourg SUMO Traffic (LuST) simulation. Following this idea, starting from the Monaco SUMO Traffic (MoST) Scenario, we used the administrative boundaries provided by OpenStreetMap (OSM) [15] to partition the data corresponding to the different mobility patterns associated with different traffic assignments, to assess the comparability of the resulting MFDs.…”

Section: Introductionmentioning

confidence: 99%

Comparing Multi-Modal Traffic Assignments in Large-Scale Simulations using the Macroscopic Fundamental Diagram: Mode Shift from Cars to Powered Two Wheelers

Codecà

Viti

Cahill

et al. 2021

2021 7th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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How Road and Mobile Networks Correlate: Estimating Urban Traffic Using Handovers

Cited by 6 publications

References 31 publications

Prediction of User Throughput in the Mobile Network Along the Motorway and Trunk Road

Prediction of User Throughput in the Mobile Network Along the Motorway and Trunk Road

Toward a Cost-Effective Motorway Traffic State Estimation From Sparse Speed and GPS Data

Comparing Multi-Modal Traffic Assignments in Large-Scale Simulations using the Macroscopic Fundamental Diagram: Mode Shift from Cars to Powered Two Wheelers

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