Paper Citation Record · LEDGER

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making

As of 18 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.23023.

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

pith.paper-citation-record.v1
2506.23023 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:57:39.141744Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

22 of 22 outbound references displayed

verified exact2
verified fuzzy13
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c15413aa-4bd4-4e23-9987-5a88a2aec4d8 · outbound

This paper cites Improving passenger experience and trust in automated vehicles through user- adaptive hmis: “the more the better.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Improving passenger experience and trust in automated vehicles through user- adaptive hmis: “the more the better

Reference 1

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T21:57:39.844149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1afa3f0f-5ca2-40bc-b246-fbf4e5a9a7fb · outbound

This paper cites Scenario- and model-based systems engineering for highly automated driving,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Scenario- and model-based systems engineering for highly automated driving,

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T21:57:39.322693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cff4d967-d90a-4823-a5dd-45696b01276e · outbound

This paper cites Mastering the game of go with deep neural networks and tree search,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Mastering the game of go with deep neural networks and tree search,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:37.363240Z

Source-reported events for the cited work

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Observation 7e896a20-5a2c-4a5f-b6c6-f3a7fb45c5f6 · outbound

This paper cites Survey of deep reinforcement learning for motion planning of autonomous vehicles,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Survey of deep reinforcement learning for motion planning of autonomous vehicles,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:42.731232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6c757a8a-c622-40f9-9412-d8277fbbaaf3 · outbound

This paper cites Combining deep reinforcement learning with rule-based constraints for safe highway driving,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Combining deep reinforcement learning with rule-based constraints for safe highway driving,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:42.597957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation deb5b73d-9e6a-4d36-b0f5-8bb3538f37bf · outbound

This paper cites Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:37.722224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95ff0850-1684-4676-9de2-6dd5eb6bd0f1 · outbound

This paper cites Imitation is not enough: Ro- bustifying imitation with reinforcement learning for challenging driving scenarios,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Imitation is not enough: Ro- bustifying imitation with reinforcement learning for challenging driving scenarios,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:42.424736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8321c5b2-9cd2-46e2-8c29-f7edf19915b4 · outbound

This paper cites Dynamic trajectory planning with dynamic constraints: A’state-time space’approach,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Dynamic trajectory planning with dynamic constraints: A’state-time space’approach,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:42.197866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0af5c4e9-39c4-427e-b2fb-dbee5b507a12 · outbound

This paper cites Search-based optimal motion planning for automated driving,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Search-based optimal motion planning for automated driving,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:41.931952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 50543fb7-9adf-41f6-86a8-874b5f09e1d9 · outbound

This paper cites A minimax-based decision-making approach for safe maneuver planning in automated driving,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making A minimax-based decision-making approach for safe maneuver planning in automated driving,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:41.657792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 54bc000c-4d9e-49fb-bd8b-811a594fd632 · outbound

This paper cites Alvinn: An autonomous land vehicle in a neural network,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Alvinn: An autonomous land vehicle in a neural network,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:38.036331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3588afa-a24c-421c-ab38-7ead79888d78 · outbound

This paper cites Symphony: Learning realistic and diverse agents for autonomous driving simulation,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Symphony: Learning realistic and diverse agents for autonomous driving simulation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:41.452070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6956b407-5bbe-4d42-b348-2244586bb0ba · outbound

This paper cites Safe reinforcement learning via shielding,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Safe reinforcement learning via shielding,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:41.283298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 47f22515-f9c0-481e-b6fd-6ac198920f3b · outbound

This paper cites Safetynet: Safe planning for real-world self-driving vehicles using machine-learned policies,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Safetynet: Safe planning for real-world self-driving vehicles using machine-learned policies,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:41.061251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f9161e8-64d9-47e2-ab4f-901f04ad0bc1 · outbound

This paper cites Commonroad: Composable benchmarks for motion planning on roads,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Commonroad: Composable benchmarks for motion planning on roads,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:40.788998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf7867a6-e08a-497b-b57a-16de1fc84ad1 · outbound

This paper cites Un regulation no. 157 - automated lane keeping systems (alks),.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Un regulation no. 157 - automated lane keeping systems (alks),

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:40.580692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation abd91391-5ed4-47b3-a0a1-84a0f46feaa5 · outbound

This paper cites A framework for definition of logical scenarios for safety assurance of automated driving,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making A framework for definition of logical scenarios for safety assurance of automated driving,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:38.691841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87b9d2b3-f97b-4c5e-bf0e-9141ea857bb6 · outbound

This paper cites Commonroad drivability checker: Simplifying the development and validation of motion planning algorithms,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Commonroad drivability checker: Simplifying the development and validation of motion planning algorithms,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:40.365562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dee35477-c186-4809-9ca6-6d94c52ccef9 · outbound

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

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:57:40.113266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 24e608c9-6e24-4d88-97e2-f27d46f90c67 · outbound

This paper cites Automatic Traffic Scenario Conversion from OpenSCENARIO to CommonRoad.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Automatic Traffic Scenario Conversion from OpenSCENARIO to CommonRoad

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:57:39.523443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0cd6be3d-b08c-4b59-8aae-7780efd3476d · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:39.073218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1efb53ab-f571-4bd6-b19e-5dc1fc76e4ae · outbound

This paper cites Stable-baselines3: Reliable reinforcement learning implementa- tions,.

Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making Stable-baselines3: Reliable reinforcement learning implementa- tions,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:39.141744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.