Paper Citation Record · LEDGER

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data

As of 19 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2501.03492.

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

pith.paper-citation-record.v1
2501.03492 v2

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:55.138530Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:52:26.209678Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T14:52:26.261553Z

Reference resolution

60 of 60 outbound references displayed

verified exact0
verified fuzzy40
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afdd9752-adc6-4295-be32-97552eb44922 · outbound

This paper cites Dynamic route planning with real-time traffic predictions,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Dynamic route planning with real-time traffic predictions,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:56.064406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 386f4116-a216-4fb6-9f43-170e71bc5e9a · outbound

This paper cites Multi-task federated learning for traffic prediction and its application to route planning,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Multi-task federated learning for traffic prediction and its application to route planning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:56.046583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b3453c76-2f5c-4e77-bcf6-bb46db8e484c · outbound

This paper cites An urban traffic signal control system based on traffic flow prediction,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data An urban traffic signal control system based on traffic flow prediction,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:56.028161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 09ea8c82-12c1-4427-a9a3-6ec2b99586ef · outbound

This paper cites Real-time planning of platoons coordination decisions based on traffic prediction,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Real-time planning of platoons coordination decisions based on traffic prediction,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:56.009646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4c4c91b1-6df2-45a2-9b03-bfd75fe2b294 · outbound

This paper cites Traffic management for major events,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic management for major events,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.992264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 962a613a-0a6d-4169-83c3-5584bc83b9d2 · outbound

This paper cites Traffic-prediction- based optimal control of electric and autonomous buses,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic-prediction- based optimal control of electric and autonomous buses,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.973750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2288d683-117e-4fdb-93a6-03f4518d4235 · outbound

This paper cites Controllable path planning and traffic scheduling for emergency services in the internet of vehicles,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Controllable path planning and traffic scheduling for emergency services in the internet of vehicles,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.958709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c3a926e-9d31-4746-b535-154257dbf218 · outbound

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

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Diffusion convolutional recurrent neural network: Data-driven traffic forecasting,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.876293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9b42131-7b4f-4fa6-aea0-1040a4a0ef58 · outbound

This paper cites Urban traffic monitoring and analysis using unmanned aerial vehicles (uavs): A systematic literature review,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Urban traffic monitoring and analysis using unmanned aerial vehicles (uavs): A systematic literature review,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.881303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d0d310f-60ea-4876-84c3-b9da23288c53 · outbound

This paper cites On the new era of urban traffic monitoring with massive drone data: The pneuma large-scale field experiment,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data On the new era of urban traffic monitoring with massive drone data: The pneuma large-scale field experiment,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.920451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0335fa30-a580-486f-8d57-444319d6c4b1 · outbound

This paper cites Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.891237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9174a184-e5f6-4ed1-8d99-b971cf9dfafd · outbound

This paper cites Traffic congestion and noise emissions with detailed vehicle trajectories from uavs,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic congestion and noise emissions with detailed vehicle trajectories from uavs,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.902915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 422c7115-4f60-48c6-ac56-dc4718ecbbfc · outbound

This paper cites Em- pirical observations of multi-modal network-level models: Insights from the pneuma experiment,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Em- pirical observations of multi-modal network-level models: Insights from the pneuma experiment,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.886069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5c4fee03-5c75-473d-b8f4-88bde3706efb · outbound

This paper cites Tracking the source of congestion based on a probabilistic sensor flow assignment model,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Tracking the source of congestion based on a probabilistic sensor flow assignment model,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.869940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2d0eb0e-593d-4e88-8d59-53d3ad61e941 · outbound

This paper cites Towards robust car-following based on deep reinforcement learning,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Towards robust car-following based on deep reinforcement learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.854101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c3f67905-8e65-4b73-aebd-f2399bcaa493 · outbound

This paper cites Evaluating a signalized intersection per- formance using unmanned aerial data,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Evaluating a signalized intersection per- formance using unmanned aerial data,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.837379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d7a116bd-6d75-4288-8ada-7006beac432c · outbound

This paper cites Monitoring outdoor parking in urban areas with unmanned aerial vehicles,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Monitoring outdoor parking in urban areas with unmanned aerial vehicles,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.821977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35f0b947-efb3-44ec-a979-88af735f1ecf · outbound

This paper cites How accurate are small drones for measuring microscopic traffic parameters?.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data How accurate are small drones for measuring microscopic traffic parameters?

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.805777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57097d45-cba4-4396-b608-14c93d39e129 · outbound

This paper cites Short-term traffic forecasting: Where we are and where we are going,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Short-term traffic forecasting: Where we are and where we are going,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.788371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a60b1bc1-69e0-46b9-8a87-c852df69bef9 · outbound

This paper cites Traffic flow prediction with big data: A deep learning approach,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic flow prediction with big data: A deep learning approach,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.772282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 15bcdf69-1679-41b8-86b1-c20f94b7f1a4 · outbound

This paper cites Spatio-temporal graph neural networks for predictive learning in urban computing: A survey,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Spatio-temporal graph neural networks for predictive learning in urban computing: A survey,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.945605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c24f99e0-365e-46e2-8241-c81e4aaedca4 · outbound

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

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.747177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d02dade4-9acb-4f4a-80f6-807f2a2de071 · outbound

This paper cites T-gcn: A temporal graph convolutional network for traffic prediction,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data T-gcn: A temporal graph convolutional network for traffic prediction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.732298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c63c4f39-237c-4e8d-9048-9b31da4001c9 · outbound

This paper cites Graph WaveNet for Deep Spatial-Temporal Graph Modeling.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Graph WaveNet for Deep Spatial-Temporal Graph Modeling

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.959283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0d21e1d-1a93-4569-ba9b-5acf2cfc5391 · outbound

This paper cites Attention based spatial- temporal graph convolutional networks for traffic flow forecasting,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Attention based spatial- temporal graph convolutional networks for traffic flow forecasting,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.717506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8c692de-28cc-41f6-bbfa-e03b82588cbf · outbound

This paper cites Adaptive graph convolutional recurrent network for traffic forecasting,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Adaptive graph convolutional recurrent network for traffic forecasting,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.968739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8f903b2-86fa-4d87-b990-fddebaef928f · outbound

This paper cites Con- necting the dots: Multivariate time series forecasting with graph neural networks,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Con- necting the dots: Multivariate time series forecasting with graph neural networks,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:54.973279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6989657f-3da9-4019-bfb1-2944a36b5a44 · outbound

This paper cites Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.678998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e51bb3b-b771-4db9-b770-8b537f91b1d3 · outbound

This paper cites Gman: A graph multi-attention network for traffic prediction,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Gman: A graph multi-attention network for traffic prediction,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.662841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 563ab177-0bf9-411b-8445-528a2da5d84c · outbound

This paper cites Tworesnet: Two-level resolution neural network for traffic forecasting of freeway networks,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Tworesnet: Two-level resolution neural network for traffic forecasting of freeway networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.646837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0be0b941-9709-4779-b13a-9765d9fe9372 · outbound

This paper cites Traffic graph convolutional recurrent neural network: A deep learning framework for network- scale traffic learning and forecasting,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic graph convolutional recurrent neural network: A deep learning framework for network- scale traffic learning and forecasting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.630464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ab6c4fc-32c1-4bc8-8b47-d6b0f7332cc3 · outbound

This paper cites Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecasting,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecasting,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.612779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 195b6e5c-d690-495c-9a2b-9641525d1e00 · outbound

This paper cites Attention is all you need,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Attention is all you need,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.003848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c8c1cd5-7149-4c1e-8e33-9790c4ab1bd5 · outbound

This paper cites Learning dynamic and hierarchical traffic spatiotemporal features with transformer,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Learning dynamic and hierarchical traffic spatiotemporal features with transformer,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.583431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff2220e6-7d53-4d30-ae00-d9ca5e08ab79 · outbound

This paper cites Long short-term memory,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Long short-term memory,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.014320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67e1e4d6-c20b-4a88-8fc8-339fa2aebb46 · outbound

This paper cites Spatial-Temporal Transformer Networks for Traffic Flow Forecasting.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Spatial-Temporal Transformer Networks for Traffic Flow Forecasting

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.019729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7648de1d-afa0-4792-b7d9-75b124d3da1d · outbound

This paper cites Meta graph trans- former: A novel framework for spatial–temporal traffic prediction,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Meta graph trans- former: A novel framework for spatial–temporal traffic prediction,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.557491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 46805439-3ab9-4d11-8075-0ed0712b605e · outbound

This paper cites Pre-training enhanced spatial- temporal graph neural network for multivariate time series forecasting,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Pre-training enhanced spatial- temporal graph neural network for multivariate time series forecasting,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.542689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 92785b72-9ce5-4f60-aa4d-46c1ebb1faf2 · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Masked au- toencoders are scalable vision learners,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.034175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7695cf0-91f3-4635-a05e-096d051b1755 · outbound

This paper cites Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.038690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4b13eaa-e05a-4c58-a81a-7e0d75b29b3c · outbound

This paper cites Real-time travel time prediction using multi-level k-nearest neighbor algorithm and data fusion method,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Real-time travel time prediction using multi-level k-nearest neighbor algorithm and data fusion method,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.505100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 85a3ab74-9277-4874-b611-ee7187bbc11f · outbound

This paper cites Traffic state and emission estima- tion for urban expressways based on heterogeneous data,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic state and emission estima- tion for urban expressways based on heterogeneous data,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.489647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation edcff4d6-1601-4d41-8141-16fead7cbe17 · outbound

This paper cites Improving urban traffic speed prediction using data source fusion and deep learning,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Improving urban traffic speed prediction using data source fusion and deep learning,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.471767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cfc79a9b-5d7f-438b-b84c-f3781f3a404e · outbound

This paper cites Real- time traffic state estimation in urban corridors from heterogeneous data,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Real- time traffic state estimation in urban corridors from heterogeneous data,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.455079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe5ea8cb-ba4f-4018-8b7c-d3c1c50f2336 · outbound

This paper cites Urban link travel time estimation using traffic states-based data fusion,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Urban link travel time estimation using traffic states-based data fusion,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.437930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5dce5209-daeb-4bea-962b-32c8ae525a57 · outbound

This paper cites Improving traffic flow pre- diction with weather information in connected cars: A deep learning approach,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Improving traffic flow pre- diction with weather information in connected cars: A deep learning approach,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.421828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c90e9d7c-7a15-4b47-8a44-fa22ad814ed0 · outbound

This paper cites Travel time prediction: Based on gated recurrent unit method and data fusion,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Travel time prediction: Based on gated recurrent unit method and data fusion,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.406371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e2aad27-279a-47ec-aaf3-ad8fa70f803d · outbound

This paper cites Spatial-temporal identity: A simple yet effective baseline for multivariate time series forecasting,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Spatial-temporal identity: A simple yet effective baseline for multivariate time series forecasting,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.076208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4893e382-86e8-4bfe-bed5-30d2b44b1b12 · outbound

This paper cites Are transformers effective for time series forecasting?.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Are transformers effective for time series forecasting?

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.080895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68190b5a-37c8-40b2-8279-5b1223746b84 · outbound

This paper cites Set functions for time series,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Set functions for time series,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.370486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 70b57e8e-9630-47bf-8226-a6e536c0abe9 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Semi-Supervised Classification with Graph Convolutional Networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.090010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5055a879-3118-43eb-857b-bda50ec91ac4 · outbound

This paper cites Layer Normalization.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Layer Normalization

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.094953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d694275b-c054-49d5-933c-7b6296f7369d · outbound

This paper cites The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.100474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddc132e3-d4ff-4e26-9a88-1699737743d2 · outbound

This paper cites Traffic simulation with aimsun,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Traffic simulation with aimsun,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.345477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation afb90ef4-d24a-4827-9bda-daf620fcde01 · outbound

This paper cites Two-layer adaptive sig- nal control framework for large-scale dynamically-congested networks: Combining efficient max pressure with perimeter control,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Two-layer adaptive sig- nal control framework for large-scale dynamically-congested networks: Combining efficient max pressure with perimeter control,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.111986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9daf492e-7e0b-4941-8706-2fc7a9e9ab28 · outbound

This paper cites Enhancing model- based feedback perimeter control with data-driven online adaptive op- timization,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Enhancing model- based feedback perimeter control with data-driven online adaptive op- timization,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:55.117284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f501879b-fba5-4e25-853a-331aff2f1b3b · outbound

This paper cites an unresolved cited work.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-10T21:56:55.309707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 813f9ea4-953c-424d-8dd5-a89856c86193 · outbound

This paper cites Under- standing traffic capacity of urban networks,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Under- standing traffic capacity of urban networks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.294755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 55361f95-89df-4c49-abc2-77fb854c079f · outbound

This paper cites Clustering of heterogeneous networks with directional flows based on “snake.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Clustering of heterogeneous networks with directional flows based on “snake

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.280284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db4d8b50-c524-462c-98ac-f78208e6a2bd · outbound

This paper cites Urban network gridlock: Theory, characteristics, and dynamics,.

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data Urban network gridlock: Theory, characteristics, and dynamics,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:55.265407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 27d91b79-9646-407b-8aa2-ce2912ab6c65 · inbound

Ctx2TrajGen: Traffic Context-Aware Microscale Vehicle Trajectories using Generative Adversarial Imitation Learning cites this paper.

Ctx2TrajGen: Traffic Context-Aware Microscale Vehicle Trajectories using Generative Adversarial Imitation Learning Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:52:26.269131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.