Paper Citation Record · LEDGER

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics

As of 8 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2505.21818.

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

pith.paper-citation-record.v1
2505.21818 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:30:22.815359Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy29
unresolved2
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2a7d6706-bcc5-4448-9ebf-6c0291aa8af1 · outbound

This paper cites A comparison of the accumulation-based, trip-based and time delay macroscopic fundamental diagram models,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics A comparison of the accumulation-based, trip-based and time delay macroscopic fundamental diagram models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:29.725569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a0009e40-6081-4e37-b5c8-7b28f27db520 · outbound

This paper cites On the spatial partitioning of urban trans- portation networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics On the spatial partitioning of urban trans- portation networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:29.625937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f646c95-d367-4bd9-bb7d-07d6fada3d5f · outbound

This paper cites Urban gridlock: Macroscopic modeling and mitigation approaches,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Urban gridlock: Macroscopic modeling and mitigation approaches,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:29.408111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a97fb3c-9263-4562-8bd2-ce86fe80451c · outbound

This paper cites Optimal perimeter control for two urban regions with macroscopic fundamental diagrams: A model predictive approach,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Optimal perimeter control for two urban regions with macroscopic fundamental diagrams: A model predictive approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:29.172780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d5ceb25-87cd-4609-876f-395058147d92 · outbound

This paper cites Analytical optimal solution of perimeter traffic flow control based on mfd dynamics: A pontryagin’s maximum principle approach,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Analytical optimal solution of perimeter traffic flow control based on mfd dynamics: A pontryagin’s maximum principle approach,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:28.938085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 35c0a70a-dd0e-4a9a-9bae-98f7d1b3738d · outbound

This paper cites Perimeter and boundary flow control in multi-reservoir heterogeneous networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Perimeter and boundary flow control in multi-reservoir heterogeneous networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:28.844864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca07162e-1472-4b48-a6e1-dad0750bfb7a · outbound

This paper cites Multiple concentric gating traffic control in large-scale urban networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Multiple concentric gating traffic control in large-scale urban networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:28.736694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a2701c2e-05ac-4d2e-9228-faacbba565f1 · outbound

This paper cites Adaptive perimeter traffic control of urban road networks based on MFD model with time delays,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Adaptive perimeter traffic control of urban road networks based on MFD model with time delays,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:28.634306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c31abfcb-18a5-47aa-ae3c-dc4c124d9a63 · outbound

This paper cites Robust constrained control of uncertain macroscopic fun- damental diagram networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Robust constrained control of uncertain macroscopic fun- damental diagram networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:28.507343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation baf2037e-d37a-452c-ab91-56a8d1fc1dd8 · outbound

This paper cites Robust perimeter control for two urban regions with macroscopic fundamental diagrams: a control-lyapunov function approach,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Robust perimeter control for two urban regions with macroscopic fundamental diagrams: a control-lyapunov function approach,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:28.054923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36b0cef1-a97b-43c1-9524-5f53627dc2a9 · outbound

This paper cites Boundary conditions and behavior of the macroscopic fundamental diagram based network traffic dynamics: A control systems perspective,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Boundary conditions and behavior of the macroscopic fundamental diagram based network traffic dynamics: A control systems perspective,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:27.784751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 78e8f237-7986-45a8-a253-d080edef383a · outbound

This paper cites Feedback perimeter control with online estimation of maximum throughput for an incident-affected road network,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Feedback perimeter control with online estimation of maximum throughput for an incident-affected road network,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:27.430209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2081b0df-38a1-46c2-a84a-0bc346c453d2 · outbound

This paper cites H ∞ robust perimeter flow control in urban networks with partial information feedback,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics H ∞ robust perimeter flow control in urban networks with partial information feedback,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:27.117800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6ae60ca3-1fa4-4773-b712-6b0bee927bcf · outbound

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

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Enhancing model- based feedback perimeter control with data-driven online adaptive op- timization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:26.885323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e20c01d4-b0ae-44d6-8fa9-bd4c3b855d9e · outbound

This paper cites Enhancing the performance of existing urban traffic light control through extremum-seeking,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Enhancing the performance of existing urban traffic light control through extremum-seeking,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:26.434904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 465a03d7-867c-4d10-aa45-fc6fc29fe901 · outbound

This paper cites Two-level hierarchical optimal control for urban traffic networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Two-level hierarchical optimal control for urban traffic networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:26.184748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f5dd1a3-9ee8-4ca7-882b-ce07492fb13e · outbound

This paper cites Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:25.935038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eec2c753-508a-4129-9957-93d44acd3e34 · outbound

This paper cites Distributed model-free adaptive predictive control for urban traffic networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Distributed model-free adaptive predictive control for urban traffic networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:25.675347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8ee8c2a2-f53e-41c8-ac89-a44bf28a6551 · outbound

This paper cites Model-free perimeter metering control for two-region urban networks using deep reinforcement learning,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Model-free perimeter metering control for two-region urban networks using deep reinforcement learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:25.294913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f859959e-78c0-41c5-bd48-ca242b4cc172 · outbound

This paper cites Neuro-dynamic programming for optimal control of macroscopic fun- damental diagram systems,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Neuro-dynamic programming for optimal control of macroscopic fun- damental diagram systems,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:24.977936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7473a870-86f4-4e8f-ac88-2931a7e64b30 · outbound

This paper cites Data efficient reinforcement learning and adaptive optimal perimeter control of network traffic dynamics,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Data efficient reinforcement learning and adaptive optimal perimeter control of network traffic dynamics,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:24.735765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c07196ad-88fa-4d85-8846-323d668bb688 · outbound

This paper cites An iterative adaptive dynamic programming approach for macroscopic fundamental diagram-based perimeter control and route guidance,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics An iterative adaptive dynamic programming approach for macroscopic fundamental diagram-based perimeter control and route guidance,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:24.506878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6019f535-09cd-4fef-b7bf-cdc15f8bf7bf · outbound

This paper cites Coordinated distributed adaptive perimeter control for large-scale urban road networks,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Coordinated distributed adaptive perimeter control for large-scale urban road networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:24.270492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d70d326-92ce-47cb-9908-c40fd035cd98 · outbound

This paper cites Adaptive perimeter control for multi-region accumulation-based models with state delays,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Adaptive perimeter control for multi-region accumulation-based models with state delays,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:24.125868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 764c6b13-723f-404f-88a8-447ab5e16ab7 · outbound

This paper cites Hierarchical control for stochastic network traffic with reinforcement learning,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Hierarchical control for stochastic network traffic with reinforcement learning,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:30:22.254833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fad4663-fff0-4225-bcad-4214a822e438 · outbound

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

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Two-layer adaptive sig- nal control framework for large-scale dynamically-congested networks: Combining efficient max pressure with perimeter control,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:23.935482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c08c835-67d8-4410-a642-db84b2d7fed2 · outbound

This paper cites Tracking control optimization scheme of continuous-time nonlinear system via online single network adaptive critic design method,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Tracking control optimization scheme of continuous-time nonlinear system via online single network adaptive critic design method,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:23.736050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c446c596-ab55-423b-b6c5-d74e2c703ef1 · outbound

This paper cites Near-optimal output tracking controller design for nonlinear systems using an event-driven adp approach,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Near-optimal output tracking controller design for nonlinear systems using an event-driven adp approach,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:23.501230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96d42201-bc14-415a-9ba3-c98534090a5f · outbound

This paper cites Reinforcement learning and adaptive dynamic programming for feedback control,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Reinforcement learning and adaptive dynamic programming for feedback control,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:23.301769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 171b32de-6016-4e75-850c-5a4a298cab7c · outbound

This paper cites Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:30:22.746551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47698d26-1e4d-45af-abe1-c6ac837cb3fd · outbound

This paper cites Calibration and uncertainty quantification of macroscopic fundamental diagrams,.

Learning-Based Tracking Perimeter Control for Two-region Macroscopic Traffic Dynamics Calibration and uncertainty quantification of macroscopic fundamental diagrams,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:23.072803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.