Paper Citation Record · LEDGER

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation

As of 10 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2606.07556.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.07556 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T19:55:12.763334Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab016608-1efb-40d4-b5eb-7b37cf329314 · outbound

This paper cites Intelligent transportation systems for sustainable smart cities,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Intelligent transportation systems for sustainable smart cities,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 8f290d0c-9c38-4011-8b19-100b3cf20b8a · outbound

This paper cites Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities,

Reference 2

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Observation 191955e9-f11e-46c2-b534-37a87ac8eb20 · outbound

This paper cites City-wide traffic volume inference with loop detector data and taxi trajectories,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation City-wide traffic volume inference with loop detector data and taxi trajectories,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 59fcbb8c-c126-412d-a3c7-e436eab12105 · outbound

This paper cites Using gps technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Using gps technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment,

Reference 5

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Observation abe2c398-71c2-40ec-9bc2-95169d759ff2 · outbound

This paper cites Estimating human trajectories and hotspots through mobile phone data,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Estimating human trajectories and hotspots through mobile phone data,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 619c6ad7-e125-4604-b8c9-d377652a6ce2 · outbound

This paper cites Estimating total traffic volume with statistical modeling approach,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Estimating total traffic volume with statistical modeling approach,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 8e2d54f6-d3b0-4916-8e1d-5a5f7d05df7a · outbound

This paper cites A digital twin smart city for citizen feedback,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation A digital twin smart city for citizen feedback,

Reference 8

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Observation 5e240da0-ce21-4db4-a597-5f4768358cf7 · outbound

This paper cites Getting real: the challenge of building and validating a large-scale digital twin of barcelona’s traffic with empirical data,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Getting real: the challenge of building and validating a large-scale digital twin of barcelona’s traffic with empirical data,

Reference 9

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Observation e62bfb7f-9773-4620-8ca8-96d170051ecd · outbound

This paper cites A Transportation Digital-Twin Approach for Adaptive Traffic Control Systems.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation A Transportation Digital-Twin Approach for Adaptive Traffic Control Systems

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-29T20:03:56.413992Z

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Observation b830dfb3-6c46-4411-84cd-919c84a0a0a3 · outbound

This paper cites Cooperative ramp merging design and field implementation: a digital twin approach based on vehicle-to-cloud communication,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Cooperative ramp merging design and field implementation: a digital twin approach based on vehicle-to-cloud communication,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation f7c4b36a-b72a-4318-8396-4bfc335abd08 · outbound

This paper cites Enhancing traffic safety analysis with digital twin technology: integrating vehicle dynamics and environmental factors into microscopic traffic simulation,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Enhancing traffic safety analysis with digital twin technology: integrating vehicle dynamics and environmental factors into microscopic traffic simulation,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 94e7c7a5-e099-462b-9116-275c582b40e3 · outbound

This paper cites Adaptive optimization of traffic sensor locations under uncertainty using flow-constrained inference,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Adaptive optimization of traffic sensor locations under uncertainty using flow-constrained inference,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 0e4fa5e7-3277-457f-9f00-4231fc671d53 · outbound

This paper cites Spatial prediction of traffic levels in unmeasured locations: applications of universal kriging and geograph- ically weighted regression,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Spatial prediction of traffic levels in unmeasured locations: applications of universal kriging and geograph- ically weighted regression,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation eccaca0f-a26a-4cb9-8652-3fa997417ba1 · outbound

This paper cites Location–allocation strategies for traffic coun- ters—a citywide deployment,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Location–allocation strategies for traffic coun- ters—a citywide deployment,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 79cf0123-6064-4a7d-a561-a517c6dd64da · outbound

This paper cites On estimation of a probability density function and mode,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation On estimation of a probability density function and mode,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 2ecef4ea-0fb5-4b91-89b2-ed039bb85a6e · outbound

This paper cites Urban network-wide traffic volume estimation under sparse deployment of detectors,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Urban network-wide traffic volume estimation under sparse deployment of detectors,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 07cde702-e9a0-4444-8441-1a00449c29ca · outbound

This paper cites Diffusion convolutional recurrent neural network: Data-driven traffic forecasting,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Diffusion convolutional recurrent neural network: Data-driven traffic forecasting,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 595b67fb-abac-4082-9ca2-28686068c2b4 · outbound

This paper cites Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 075b81ef-b547-478f-8745-843f32126f8c · outbound

This paper cites Graph wavenet for deep spatial-temporal graph modeling,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Graph wavenet for deep spatial-temporal graph modeling,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 61f59801-9df2-45c1-bdea-b0973f1e53b1 · outbound

This paper cites Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-28T02:23:22.451311Z

Source-reported events for the cited work

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Observation f2caddf7-4ac7-4e08-b9e5-9e66405eeec0 · outbound

This paper cites Sensor selection via convex optimization,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Sensor selection via convex optimization,

Reference 23

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Observation 7a519915-3508-4c42-9b9f-1c82e3017189 · outbound

This paper cites A submodular approach for optimal sensor placement in traffic networks,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation A submodular approach for optimal sensor placement in traffic networks,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation ee4de4d1-9a71-43e1-85b7-f99bbc3a43a5 · outbound

This paper cites Submodularity of optimal sen- sor placement for traffic networks,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Submodularity of optimal sen- sor placement for traffic networks,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation e1eb64c3-78ff-4a54-916a-b9b7d0ecc436 · outbound

This paper cites Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical stud- ies,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical stud- ies,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation c328ab65-7aaa-499c-8617-3d7d7f89606c · outbound

This paper cites Optimization of traffic sensor location for complete link flow observability in traffic network considering sensor failure,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Optimization of traffic sensor location for complete link flow observability in traffic network considering sensor failure,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation f9cf73f4-2d43-493e-a28a-acf55be85990 · outbound

This paper cites Unsupervised scalable representation learning for multivariate time series,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Unsupervised scalable representation learning for multivariate time series,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation d48493a8-ea45-4620-8222-601466630300 · outbound

This paper cites Time-series representation learning via temporal and contextual con- trasting,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Time-series representation learning via temporal and contextual con- trasting,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 830d66a1-d745-40dc-873d-27a43e85b9f6 · outbound

This paper cites doi:10.1109/TPAMI.2024.3387317.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation doi:10.1109/TPAMI.2024.3387317

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T20:03:56.142982Z

Source-reported events for the cited work

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Observation 665f6cbf-7273-472c-ba2d-de3e64394ae5 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation A simple framework for contrastive learning of visual representations,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 54f9a937-d783-4419-b2bc-7ca626bb65f5 · outbound

This paper cites Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting , url=.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting , url=

Reference 32

Resolution: verified exact; doi, observed 2026-06-29T20:03:56.144964Z

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Observation 00690ac6-63f8-42b5-9295-929cf74b2ddb · outbound

This paper cites Graph wavenet for deep spatial-temporal graph modeling,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Graph wavenet for deep spatial-temporal graph modeling,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 421d40b2-5dc0-4832-b298-d6bc65388ada · outbound

This paper cites 1907–1913.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation 1907–1913

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation af50ecc9-0556-428e-b0a3-44957ea36276 · outbound

This paper cites Visualizing data using t-SNE,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Visualizing data using t-SNE,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation a5d72996-9d92-4d10-9dc9-59efd61ef331 · outbound

This paper cites A tutorial on kernel density estimation and recent ad- vances,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation A tutorial on kernel density estimation and recent ad- vances,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation 41cc9691-b133-4817-bcb2-00317c4cde45 · outbound

This paper cites Cross-sectional traffic volume for general roads,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation Cross-sectional traffic volume for general roads,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Observation c33a51c6-09b6-4312-8426-b89ad0919ec7 · outbound

This paper cites OpenStreetMap Copyright and License,.

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation OpenStreetMap Copyright and License,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-29T19:55:12.763334Z

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Pith citing papers

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