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Paper Citation Record · LEDGER

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control

As of 12 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2509.25515.

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

pith.paper-citation-record.v1
2509.25515 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T11:50:27.298728Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

34 of 34 outbound references displayed

  • verified exact5
  • verified fuzzy29
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 92fd994f-fc66-42d4-a9f0-0eb0554f89d1 · outbound

This paper cites Urban traffic congestion: Its causes-consequences-mitigation.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Urban traffic congestion: Its causes-consequences-mitigation

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.512516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:b9beb96e0cf2bc40339b4b41a0bcf50473c6f984ef728d1eb9adce089d73ccc0

Observation 1fd5636c-563b-4c54-9fc7-62b240d72052 · outbound

This paper cites Real-world CO 2 impacts of traffic congestion.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Real-world CO 2 impacts of traffic congestion

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.508985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:0b877cf907ab8eb01b6ec8e7d0927ab1fe9d0ffee34067c3e513d21dcbb1fb76

Observation 68d8586c-7125-40e0-82f3-2228abf97344 · outbound

This paper cites A safety-prioritized receding horizon control framework for platoon formation in a mixed traffic environment.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control A safety-prioritized receding horizon control framework for platoon formation in a mixed traffic environment

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.449581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:31bc1b8f8c0b475b38ad0036f21413766dfb54a08c5098c3242a106a7bfd4f0a

Observation ec13cb33-0206-4069-bcdf-aa892c5279ec · outbound

This paper cites Large-scale multi-fleet platoon coordination: A dynamic programming approach.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Large-scale multi-fleet platoon coordination: A dynamic programming approach

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.445795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:4d364421d69c636f5b45f30c681fa53b9e0fa88da514faa9aeb5fe0cf13666d7

Observation e5164a4d-310a-444f-9b49-3a73ce77528a · outbound

This paper cites Approximate dynamic programming for platoon coordination under hours-of-service regulations.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Approximate dynamic programming for platoon coordination under hours-of-service regulations

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.441747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:af0a932c51889441c730b67c386fdfed6dc75fcc385c8370aef4c414b9518b4c

Observation 0501b42a-ee38-4ff2-b2b3-7abf2e4bb8b8 · outbound

This paper cites Stochastic time-optimal trajectory planning for connected and automated vehicles in mixed-traffic merging scenarios.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Stochastic time-optimal trajectory planning for connected and automated vehicles in mixed-traffic merging scenarios

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.493196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:3bb00d5c599599f25120c85b457b94bec45a20b2d07b8aed789faf28ca58e023

Observation ad6f7472-9481-4e55-b7c4-e9089375e319 · outbound

This paper cites Optimal path planning for connected and automated vehicles at urban intersections.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Optimal path planning for connected and automated vehicles at urban intersections

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.519277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:ff4657fde4a3077f33415beb3bc4248f646be5265c0c56026546867251aa2a42

Observation 8f0d9f1b-e6d4-4414-9bc1-b45db7c3f458 · outbound

This paper cites Congestion-aware routing, rebalancing, and charging scheduling for electric autonomous mobility- on-demand system.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Congestion-aware routing, rebalancing, and charging scheduling for electric autonomous mobility- on-demand system

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.515941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:8e14888517f16338cc158527ff59af58848ef40b0c1ce163e8fa8a441566f6c0

Observation e968fe28-2cb9-42c5-bd93-8ce7818d3e6c · outbound

This paper cites Routing Guidance for Emerging Transportation Systems with Improved Dynamic Trip Equity.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Routing Guidance for Emerging Transportation Systems with Improved Dynamic Trip Equity

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:51:20.205658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:56845d920e16fac2023cd739df220837ef08b04419b2c0c10ff324439d08cc80

Observation 1ab4d656-191b-429d-8223-3ae8657b134f · outbound

This paper cites A closed-form analytical solution for optimal coordination of connected and automated vehicles.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control A closed-form analytical solution for optimal coordination of connected and automated vehicles

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.505441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:8b3990f4fb490237529d101801fe823f70a78d0e410def7be91c5f328d3329f1

Observation c0386d25-f90a-43f7-99c6-8260c604b8df · outbound

This paper cites Optimal time trajectory and coordination for connected and automated vehicles.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Optimal time trajectory and coordination for connected and automated vehicles

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.456634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:29502be3ace7be40f416325cab8bc2060e750ba6aa73bc486feefe57aad44995

Observation 2e0edb27-be4e-4961-83bc-f47cf4e5c5b0 · outbound

This paper cites A systematic review of traffic incident detection algorithms.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control A systematic review of traffic incident detection algorithms

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.478980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:560c3768f91ac530f7edf4483cf54e86f23f3c3ae8e1a4dc04b6b5be7fa4b019

Observation cf45fe24-7a1c-4130-b26f-c905a97b11d9 · outbound

This paper cites Comparative performance evaluation of incident detection algorithms.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Comparative performance evaluation of incident detection algorithms

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.471756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:c7ca999a2094d91fee601eb04c760f676c6795ebf92e599ff04b01dac724eef0

Observation 97467211-4624-4b3e-80c1-d3b4824ff003 · outbound

This paper cites Anomaly detection in road networks using sliding-window tensor factorization.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Anomaly detection in road networks using sliding-window tensor factorization

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.475438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:b4edc846c0e91c831c611ef46d3569065b5151323cd6ae97a4ecdfd6efd60084

Observation d6625a92-1f45-46dd-bd5c-86d5b05d6cfe · outbound

This paper cites Prediction-based anomaly detection method for traffic flow.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Prediction-based anomaly detection method for traffic flow

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.438129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:c22421c2fea34dcdc5d1f11946957677acac82ca7923c0607a66f775c56cb01b

Observation 737d63a2-de5b-41a9-bcd2-dbf4d87ffa52 · outbound

This paper cites Traffic anomaly detection in intelligent transport applications with time series data using informer.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Traffic anomaly detection in intelligent transport applications with time series data using informer

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.482179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:c5b71c730e182661388ace3889a62549ebd329b81fe5a9b4df067f87a06b1687

Observation 15b835c8-db77-424b-9b02-dbebbfa8d2b8 · outbound

This paper cites Urban Anomaly Analytics: Description, Detection, and Prediction.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Urban Anomaly Analytics: Description, Detection, and Prediction

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:51:20.211154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:881cda02f4ff6e640155da6dc19b541c05eb95e5ae22374068f932a4edd8db4e

Observation 52570e66-afa4-4f19-a331-fcf61f4c630a · outbound

This paper cites Traffic anomaly detection in intelligent transport applications with time series data using informer.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Traffic anomaly detection in intelligent transport applications with time series data using informer

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.525909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:eded1ab66aeddbd5a5cf8dc4898a1d8b98887ce0320dd1138467c30cfdfd6dd0

Observation 02e6119f-491c-4f49-b273-62c73d06ad22 · outbound

This paper cites Anomaly detection in traffic surveillance videos using deep learning.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Anomaly detection in traffic surveillance videos using deep learning

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.434238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:33a37fa37620752aa92fc637f3094755e662d6a105698514cfcf17b068c965a9

Observation 1fef1fa6-3f38-444e-abcb-c9d46219ef14 · outbound

This paper cites Traffic anomaly detection and video summarization using spatio-temporal rough fuzzy granulation with z-numbers.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Traffic anomaly detection and video summarization using spatio-temporal rough fuzzy granulation with z-numbers

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.522575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:195ac51abc560d466432f65f492461a927dc0cfd97677564d456383cc45a0c82

Observation f8eaf87e-eeaf-48e0-a7c1-7fb05c771172 · outbound

This paper cites Deep bilstm attention model for spatial and temporal anomaly detection in video surveillance.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Deep bilstm attention model for spatial and temporal anomaly detection in video surveillance

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.468570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:a4de2dfe42f7d6250b389ec958ab10d73995507519da873f96fb9f87c3d31a42

Observation a2f6ca81-41ce-4506-9e98-98f9b8200fda · outbound

This paper cites Pedestrian abnormal behavior detection system using edge–server architecture for large–scale CCTV environments.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Pedestrian abnormal behavior detection system using edge–server architecture for large–scale CCTV environments

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.430327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:427e8f84bf18e94fea873eb3d8419e73507e670de48215dcc2e4345a97008566

Observation fe007967-cfd9-4365-8a34-4d6a54938bd0 · outbound

This paper cites Federated variational learning for anomaly detection in multivariate time series.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Federated variational learning for anomaly detection in multivariate time series

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.488828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:6601f646603a8a867260690d3e07cae6de940aa118ec5f8d3f605d1db4c2358a

Observation 3c02e1f4-18c0-4198-8984-de28dc581186 · outbound

This paper cites Unsupervised anomaly detection for iot-based multivariate time series.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Unsupervised anomaly detection for iot-based multivariate time series

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.453067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:e3dbc0ddafcedec618071fbbb568b2670a73122d4ffe7e5b4cd2262390b47402

Observation ee47e297-5089-4d97-92c9-a7d38e063bd2 · outbound

This paper cites Unsupervised anomaly detection for cars can sensors time series.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Unsupervised anomaly detection for cars can sensors time series

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.464975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:2387432b060783d0436bf62a641540ca8f7e2e30bfcb6b5394106c5dbb6a7b3a

Observation 0dcfb253-e07d-4798-a4d7-2d8e00d7e197 · outbound

This paper cites MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time Series Anomaly Detection.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control MST-GAT: A Multimodal Spatial-Temporal Graph Attention Network for Time Series Anomaly Detection

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:51:20.226451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:667d69afb884c0a60adb1db677215087976c35d0e126c93d731f57f6c3df79ce

Observation a19ad396-e04d-484a-8c86-9427c114af34 · outbound

This paper cites DACAD: Domain adaptation contrastive learning for anomaly detection in multivariate time series.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control DACAD: Domain adaptation contrastive learning for anomaly detection in multivariate time series

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.502244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:71fd9aab593fc42752f2a002e7ce1b28699123e3da51818110f79a867813daba

Observation 2fa30824-6e8f-4132-b968-123e13b0d417 · outbound

This paper cites A survey on vehicular traffic flow anomaly detection using machine learning.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control A survey on vehicular traffic flow anomaly detection using machine learning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.499089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:14ecbb78ea06e6336dc42bc92f0a26f40285a72232a11c9e7be2647d74981398

Observation e35fa62a-f695-45cb-845c-6e9621edaff6 · outbound

This paper cites Urban anomaly analytics: Description, detection, and prediction.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Urban anomaly analytics: Description, detection, and prediction

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:51:20.216572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:03a97831a4cf7d4f64932af380d1929d00d17638c579e636a21c87a813f7c44f

Observation 17c4edc7-d608-4a9e-a65d-8c689e2a63af · outbound

This paper cites History-based road traffic anomaly detection using deep learning and real-world data.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control History-based road traffic anomaly detection using deep learning and real-world data

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.528755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:8badadb9d52904fcd48654fe274962e08cb8f90f8a154da936da230fde6de3c8

Observation e83624ff-07f6-4f88-9e50-42c4eb10ad69 · outbound

This paper cites Estimating congestion zones and travel time indexes based on floating car data.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Estimating congestion zones and travel time indexes based on floating car data

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.485506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:068d022572dd98cc59eb75cce6d56761b759191f43526ac383cdf0190c1b9892

Observation 6654b67e-b495-41b2-bf62-32e5995f1a4f · outbound

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

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Diffusion convolutional recurrent neural network: Data-driven traffic forecasting

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.496201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:b57c10fd6fbc5452dc48f5e065e93bac941cbd80326b08d7dba09e56d82b4002

Observation 23a9a928-034c-4427-a52d-1c2c03cd436a · outbound

This paper cites Second generation of pollutant emission models for SUMO.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Second generation of pollutant emission models for SUMO

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-18T11:51:20.460066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:29e355c7817b10e1a0cc70d931cda4d770c5f77bee1dd85e696bba4ccd16aa3c

Observation f00db88c-4abb-4365-9871-20d04c69a117 · outbound

This paper cites Worst-Case Control and Learning Using Partial Observations Over an Infinite Time-Horizon.

Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control Worst-Case Control and Learning Using Partial Observations Over an Infinite Time-Horizon

Reference 34

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arxiv_id, observed 2026-05-18T11:51:20.221503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T11:50:27.298728Z digest=sha256:dd7a3ecf1a19463e4b03b04e1186d84e8b98e782583b1788bb2ba0dd63e76bb6

Pith citing papers

No inbound Pith citation observations are available.