Paper Citation Record · LEDGER

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors

As of 22 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2502.00402.

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

pith.paper-citation-record.v1
2502.00402 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:11:16.964655Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:13:52.423691Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T12:13:52.508728Z

Reference resolution

46 of 46 outbound references displayed

verified exact0
verified fuzzy37
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 480d731b-4763-4631-a514-905b27b947f8 · outbound

This paper cites Planning with occluded traffic agents using bi-level variational occlusion models,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Planning with occluded traffic agents using bi-level variational occlusion models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.425119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16f2a95c-d276-4abb-ba7a-0f58658864d8 · outbound

This paper cites Activeanno3d-an active learning framework for multi-modal 3d object detection,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Activeanno3d-an active learning framework for multi-modal 3d object detection,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.833249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4ce54a0-9e98-4b04-abcd-dc7522affd3a · outbound

This paper cites Create a large-scale video driving dataset with detailed attributes using amazon sagemaker ground truth,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Create a large-scale video driving dataset with detailed attributes using amazon sagemaker ground truth,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.411169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bc6889df-9177-430c-8c61-0945b868b936 · outbound

This paper cites Fingscheidt, H.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Fingscheidt, H

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.401837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cf313086-c66d-41d5-b84b-1cd02b615094 · outbound

This paper cites Ips300+: a challenging multi-modal data sets for intersection perception system,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Ips300+: a challenging multi-modal data sets for intersection perception system,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.392392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d1b47696-314e-49fa-80a8-638cf7a709ad · outbound

This paper cites The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.847263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6da2b26e-8473-4df2-b61d-9930453f00d3 · outbound

This paper cites GraphRelate3D: Context-Dependent 3D Object Detection with Inter-Object Relationship Graphs.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors GraphRelate3D: Context-Dependent 3D Object Detection with Inter-Object Relationship Graphs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.850851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9dbe350-9062-433e-8aae-dfbd3258f3d8 · outbound

This paper cites Roadsense3d: A framework for roadside monocular 3d object detection,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Roadsense3d: A framework for roadside monocular 3d object detection,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.382901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c94cc171-b25d-4e22-9d40-6f24495b73f3 · outbound

This paper cites Infradet3d: Multi-modal 3d object detection based on roadside infrastructure camera and lidar sensors,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Infradet3d: Multi-modal 3d object detection based on roadside infrastructure camera and lidar sensors,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.373628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6bc9ea9d-23c5-4aeb-8e9f-0525ac112fcb · outbound

This paper cites Real-time and robust 3d object detection with roadside lidars,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Real-time and robust 3d object detection with roadside lidars,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.859137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60768fdc-163f-465c-bee8-14d6d528e0e1 · outbound

This paper cites A Survey of Robust 3D Object Detection Methods in Point Clouds.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors A Survey of Robust 3D Object Detection Methods in Point Clouds

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.861349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff44083b-2914-4469-b5e7-e8f2b3cc8a92 · outbound

This paper cites Real-Time and Robust 3D Object Detection Within Road-Side LiDARs Using Domain Adaptation.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Real-Time and Robust 3D Object Detection Within Road-Side LiDARs Using Domain Adaptation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.863821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45cde37a-464c-4f63-a591-608567736289 · outbound

This paper cites Traffic light detection: A learning algorithm and evaluations on challenging dataset,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Traffic light detection: A learning algorithm and evaluations on challenging dataset,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.360105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e51dea73-bc21-4755-9f99-3c2fcf2cdd7b · outbound

This paper cites Laneaf: Robust multi-lane detection with affinity fields,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Laneaf: Robust multi-lane detection with affinity fields,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.349817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d9115b92-511d-47b0-a486-c8cfe6b479d4 · outbound

This paper cites PointCompress3d – a point cloud compression framework for roadside LiDARs in intelligent transportation systems.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors PointCompress3d – a point cloud compression framework for roadside LiDARs in intelligent transportation systems

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.341609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ae73bfea-bba8-4dd2-9c10-a18012ef9796 · outbound

This paper cites GraphRelate3d: Context-dependent 3d object detection with inter- object relationship graphs.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors GraphRelate3d: Context-dependent 3d object detection with inter- object relationship graphs

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.332523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 33528d2a-ad36-44b3-91a0-1855bc7e903c · outbound

This paper cites Transfer learning from simulated to real scenes for monocular 3d object detection.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Transfer learning from simulated to real scenes for monocular 3d object detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.325136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e957848c-34b5-496e-a0d9-2ad9ce6327a3 · outbound

This paper cites Patterns of vehicle lights: Addressing complexities of camera-based vehicle light datasets and metrics,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Patterns of vehicle lights: Addressing complexities of camera-based vehicle light datasets and metrics,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.317314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2f5bb6cd-5939-46bb-b5fe-2caa8d29e087 · outbound

This paper cites Collaborative semantic occupancy prediction with hybrid feature fusion in connected automated vehicles,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Collaborative semantic occupancy prediction with hybrid feature fusion in connected automated vehicles,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.308710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 02306438-39a4-43a9-85ca-30e1ceddaf0a · outbound

This paper cites A digital twin for teleoperation of vehicles in urban environments,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors A digital twin for teleoperation of vehicles in urban environments,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.300254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cc800abb-87dc-453b-b592-841e468f668f · outbound

This paper cites Safe control transi- tions: Machine vision based observable readiness index and data-driven takeover time prediction,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Safe control transi- tions: Machine vision based observable readiness index and data-driven takeover time prediction,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.291801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4562db87-7f2d-41e8-a8c8-2149edabd9ab · outbound

This paper cites TAD: A large-scale benchmark for traffic accidents detection from video surveillance.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors TAD: A large-scale benchmark for traffic accidents detection from video surveillance

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.283378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d403c3c5-3ccf-4871-84c5-81cd81605cac · outbound

This paper cites A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.274840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a1fc7975-8506-44ec-a3df-6c09f0ff5777 · outbound

This paper cites Application of a rule-based approach in real-time crash risk prediction model devel- opment using loop detector data,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Application of a rule-based approach in real-time crash risk prediction model devel- opment using loop detector data,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.899915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71f09cb6-63be-4a73-a1de-03736da23a1f · outbound

This paper cites A data-driven approach for road accident detection in surveillance videos,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors A data-driven approach for road accident detection in surveillance videos,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.264431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9223c359-2c29-4376-a4e9-8911b4e1c8fa · outbound

This paper cites Smart city transportation: Deep learning ensemble approach for traffic accident detection,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Smart city transportation: Deep learning ensemble approach for traffic accident detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.255655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9439da82-717f-4dbe-89b3-737c426d047a · outbound

This paper cites DoTA: Unsupervised detection of traffic anomaly in driving videos,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors DoTA: Unsupervised detection of traffic anomaly in driving videos,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.247433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8531210e-b392-4167-ab56-df8a86e039a8 · outbound

This paper cites Freeway accident detec- tion and classification based on the multi-vehicle trajectory data and deep learning model,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Freeway accident detec- tion and classification based on the multi-vehicle trajectory data and deep learning model,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.231773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation dd38bd37-81ad-48ba-a3d6-b0c7e402a4ca · outbound

This paper cites Vision-based traffic accident detection and anticipation: A survey,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Vision-based traffic accident detection and anticipation: A survey,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.222388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 71c35d93-dcb8-4636-afd0-bcf30d4af487 · outbound

This paper cites Adaptive video- based algorithm for accident detection on highways,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Adaptive video- based algorithm for accident detection on highways,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.213331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a9538f47-0d72-4157-8317-608147acc722 · outbound

This paper cites Deepacci- dent: A motion and accident prediction benchmark for v2x autonomous driving,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Deepacci- dent: A motion and accident prediction benchmark for v2x autonomous driving,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.204610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 247d0ca3-43a1-4a71-8f84-ac39f0d2bc99 · outbound

This paper cites CARLA: An open urban driving simulator,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors CARLA: An open urban driving simulator,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.194331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8a574ac9-56aa-491c-8d02-0b1150ed6921 · outbound

This paper cites Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.927354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b39a53b-72ac-4826-9acb-90165851ed6b · outbound

This paper cites Pedestrian behavior maps for safety advisories: Champ framework and real-world data analysis,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Pedestrian behavior maps for safety advisories: Champ framework and real-world data analysis,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.185372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d1f0dcda-851e-4f40-a4cf-5b9c582c2c1b · outbound

This paper cites Ultralytics yolov8,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Ultralytics yolov8,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:16.934256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e867b3e6-0e06-4970-85e9-1b10a2ea4d39 · outbound

This paper cites Computer vision annotation tool (CV AT).

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Computer vision annotation tool (CV AT)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.171880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 26ba9588-fb65-417d-bf53-c772a1541e04 · outbound

This paper cites 3d bat: A semi-automatic, web-based 3d annotation toolbox for full-surround, multi-modal data streams,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors 3d bat: A semi-automatic, web-based 3d annotation toolbox for full-surround, multi-modal data streams,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.163929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation af8986a9-075c-4728-9237-874e2c6e49a9 · outbound

This paper cites A9-dataset: Multi-sensor infrastructure-based dataset for mobility re- search,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors A9-dataset: Multi-sensor infrastructure-based dataset for mobility re- search,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.156656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fd6558f6-4912-4564-9162-3b235f4df6b6 · outbound

This paper cites TUMTraf intersection dataset: All you need for urban 3d camera-LiDAR roadside perception,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors TUMTraf intersection dataset: All you need for urban 3d camera-LiDAR roadside perception,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.147637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ca6926f8-7f7b-4dbd-9cf4-cff6ef4c1ec2 · outbound

This paper cites Tumtraf event: Calibration and fusion resulting in a dataset for roadside event-based and rgb cameras,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Tumtraf event: Calibration and fusion resulting in a dataset for roadside event-based and rgb cameras,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.138893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7898ca56-da7c-4cb1-a337-77954b9ffaa0 · outbound

This paper cites Tumtraf v2x cooperative perception dataset,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Tumtraf v2x cooperative perception dataset,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.129008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3e525cf9-4d09-4935-ad29-c268689eaffe · outbound

This paper cites W ARM-3d: A weakly-supervised sim2real domain adaptation framework for roadside monocular 3d object detection.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors W ARM-3d: A weakly-supervised sim2real domain adaptation framework for roadside monocular 3d object detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.120311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 79614bdb-492f-4e4e-b719-d5083b12a337 · outbound

This paper cites TUM traffic dataset development kit.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors TUM traffic dataset development kit

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.111244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 31b8e3f7-5324-4679-b4e5-da07d3beee71 · outbound

This paper cites Vision language models in autonomous driving: A survey and outlook,.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Vision language models in autonomous driving: A survey and outlook,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.101874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fe983a5f-2aef-4891-aa2f-b46dd6230396 · outbound

This paper cites AUTOtech.agil : Architecture and technologies for orchestrating automotive agility.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors AUTOtech.agil : Architecture and technologies for orchestrating automotive agility

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.091435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3faa8362-5d5d-4fe9-a415-2e637a20d2db · outbound

This paper cites Name: IEEE Trans.

Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors Name: IEEE Trans

Reference 459

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:11:17.239879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 15fb04c6-94e7-4289-99f1-e16299cb05d6 · inbound

LangCoop: Collaborative Driving with Language cites this paper.

LangCoop: Collaborative Driving with Language Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:13:52.514630Z

Source-reported events for the cited work

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