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Paper Citation Record · LEDGER

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization

As of 13 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 2 inbound Pith citation observations for arXiv:2506.03548.

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

pith.paper-citation-record.v1
2506.03548 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:03:26.839202Z

measured 27 of 27 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T14:32:54.466546Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T14:33:30.384508Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact1
  • verified fuzzy20
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0f8cb78f-8276-454b-9c08-b7cf5a2353dc · outbound

This paper cites Intellilight: A reinforcement learning approach for intelligent traffic light control,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Intellilight: A reinforcement learning approach for intelligent traffic light control,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:30.781878Z

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=2026-08-07T11:03:24.616166Z digest=sha256:1086e02458a7106f991c1fe0da940ec44e2d7d63ed92ecb4378528c3e92818d3

Observation 5d046187-baea-44af-bce2-02b5f16f1ec1 · outbound

This paper cites Colight: Learning network-level cooperation for traffic signal control,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Colight: Learning network-level cooperation for traffic signal control,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:30.583872Z

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=2026-08-07T11:03:24.688886Z digest=sha256:eeda15683b50bf49597e5ad1d7569e2aea4d3b3ec002c4dfce2153b3c398961f

Observation 866115ca-9d9f-4b87-98b8-08c51904346d · outbound

This paper cites A semi-“smart predict, then optimize.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization A semi-“smart predict, then optimize

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:30.416279Z

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=2026-08-07T11:03:24.770619Z digest=sha256:d33e705beb382d40a67c1a7f27f397739e4d2ce52b92ddd3b89b0a455c7c0691

Observation 182380f7-2430-4f9b-8f02-c7496e7d339f · outbound

This paper cites Trafficwise: Leveraging world models for generalized and interpretable traffic control,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Trafficwise: Leveraging world models for generalized and interpretable traffic control,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:30.263971Z

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=2026-08-07T11:03:24.872002Z digest=sha256:4d7c1eb34f8784ac1947e11d5e11f4b47edd4b5ad8e2d23b4874e67fd2f8b7f2

Observation 66b5ffd4-5554-4346-863b-a0eb7b0a59e6 · outbound

This paper cites Parallel learning based foundation model for networked traffic signal control,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Parallel learning based foundation model for networked traffic signal control,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:30.061129Z

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=2026-08-07T11:03:24.936004Z digest=sha256:58673184d16ff0083f4e82eddeab6c73ee0fbd01e1ff63d370a43a1554dd4d54

Observation e8c3d2e7-4341-4b5d-a19d-04fd7cef464b · outbound

This paper cites A deep reinforcement learning based ramp metering control method considering ramp outflow,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization A deep reinforcement learning based ramp metering control method considering ramp outflow,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:29.862271Z

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=2026-08-07T11:03:25.041210Z digest=sha256:0f5fda8f0764171a64e28d6ffd84264af27eae7696b1f71b932b38a31dedd829

Observation 93bf7a86-dcbb-417b-91bf-35110856172e · outbound

This paper cites LLMLight: Large Language Models as Traffic Signal Control Agents.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization LLMLight: Large Language Models as Traffic Signal Control Agents

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:25.175086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:25.175086Z digest=sha256:3095d1af6d7af5e21c75404366b0b72634bd097bd43716d723052f431181956a

Observation edc6acd3-18be-4604-a889-39a0d0e2e9bd · outbound

This paper cites CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:25.321264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:25.321264Z digest=sha256:d797b79cc8eb3c9999b9b8bc47d02d2df06844fa0c6b2101f93ee3f38e78ad76

Observation 48452979-b077-4e5b-8730-053949679dbe · outbound

This paper cites LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:25.422257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:25.422257Z digest=sha256:a03774731251e130b888beccbcd2e0b2e93fb13d612c40c28115b53565c62165

Observation c80ec724-d01d-409e-af98-05f7bf5035b3 · outbound

This paper cites CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:03:27.079468Z

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=2026-08-07T11:03:25.500475Z digest=sha256:61fac2957f7a012806d4cf6795211ff60d0a794fccb38c12e11537c8ddcbf177

Observation 6549761a-f6da-44ef-8595-4119368a02c8 · outbound

This paper cites Large language model-assisted arterial traffic signal control,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Large language model-assisted arterial traffic signal control,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:29.651778Z

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=2026-08-07T11:03:25.576730Z digest=sha256:ce3772f5040ab9d3ffdc63d262d5a9123e33e3251f7fc2940b0e7c509554cb4b

Observation 5b11ea18-12fe-4db9-9f38-614e55142827 · outbound

This paper cites Large language model-driven urban traffic signal control,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Large language model-driven urban traffic signal control,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:29.496136Z

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=2026-08-07T11:03:25.676271Z digest=sha256:0be18a3bd7f16ba45d2a7dd218dc24c6b51c916bc0d247f1071f0e4d31f4c555

Observation 8217f561-3d11-43e2-9201-75dc00c11ea3 · outbound

This paper cites Smart mobility digital twin based automated vehicle navigation system: A proof of concept,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Smart mobility digital twin based automated vehicle navigation system: A proof of concept,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:29.289571Z

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=2026-08-07T11:03:25.757034Z digest=sha256:fe54287ef9262cfe2cae4411ead5da86e81fdf9546be07b82464f74d0f8cca05

Observation 157d1897-f280-4722-be17-e345c70d5318 · outbound

This paper cites Blame-free motion planning in hybrid traffic,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Blame-free motion planning in hybrid traffic,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:29.082790Z

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=2026-08-07T11:03:25.860281Z digest=sha256:c4ffffd1cab899b57a8ec5cc14b57156e78c33333640f4165e1946482dcaed46

Observation ac06298d-c77a-48de-8906-20560bddc9d6 · outbound

This paper cites Hptsim: A highway parallel traffic sim- ulation framework for mixed concurrency scenarios,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Hptsim: A highway parallel traffic sim- ulation framework for mixed concurrency scenarios,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:28.934039Z

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=2026-08-07T11:03:25.958006Z digest=sha256:65097ba308af3ebef27be71c4a8ad7f37c478ab7e4dca3f612fbba2c8406bcae

Observation dc425d3b-c5db-4dbe-be17-6b546b4e32c4 · outbound

This paper cites Iterative learning-based cooperative motion planning and decision-making for connected and autonomous vehicles coordination at on-ramps,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Iterative learning-based cooperative motion planning and decision-making for connected and autonomous vehicles coordination at on-ramps,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:28.707375Z

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=2026-08-07T11:03:26.070717Z digest=sha256:61a23a4f0e67dabde754947bfa8afa83fd1414bba22fe5aee1cff9c9beaab33b

Observation 7a604a0e-9f69-4754-b1aa-b4b2234439b3 · outbound

This paper cites Human-like decision making and planning for autonomous driving with reinforcement learning,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Human-like decision making and planning for autonomous driving with reinforcement learning,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:28.552213Z

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=2026-08-07T11:03:26.162805Z digest=sha256:5bd2d4fe4236e56a00e3f9946df9d6f865f56d93a661cf2c34cb429e6536d3e4

Observation 0ad8f830-65b8-45a8-8d1d-ab27b57e74c9 · outbound

This paper cites Robocar: A rapidly deploy- able open source platform for autonomous driving research,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Robocar: A rapidly deploy- able open source platform for autonomous driving research,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:28.290220Z

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=2026-08-07T11:03:26.242378Z digest=sha256:a90fbe8454ed56bd2b2597117ea12a1daa83269620d3fd553eb733445ef635e5

Observation c1dea4c6-3f66-4eec-a87f-3f6161c58b2d · outbound

This paper cites Chatsumo: Large language model for automating traffic scenario generation in simulation of urban mobility,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Chatsumo: Large language model for automating traffic scenario generation in simulation of urban mobility,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:28.081023Z

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=2026-08-07T11:03:26.318310Z digest=sha256:0802f906bf4facc6446ccb5d2a1b33074694ed6b62b9c7dee3b7c3bb4121f6f3

Observation 2b8caf2c-57a3-4fb9-b148-9fd0871d0b77 · outbound

This paper cites Open-ti: Open traffic intelligence with augmented language model,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Open-ti: Open traffic intelligence with augmented language model,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:27.910379Z

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=2026-08-07T11:03:26.394274Z digest=sha256:cc6fe578487742dc4a9ea0b74069e32a3ad0cd8e25a580e66d41b298e04c3825

Observation 598558ed-bfbc-4e0f-8978-059817c02b2c · outbound

This paper cites Introducing the model context protocol,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Introducing the model context protocol,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:27.767019Z

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=2026-08-07T11:03:26.505106Z digest=sha256:e91c6ff200e2e52f956355aa9f52ccf8ed8b142e2990040a1130c2caa7fbb06c

Observation ef4a6c0c-2231-465e-9c60-c62f78de8af5 · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversation,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Autogen: Enabling next-gen llm applications via multi-agent conversation,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:27.626855Z

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=2026-08-07T11:03:26.575498Z digest=sha256:1eac18763382bce1404e16fa1fee4e08372e6031a28a5eaf122505305ae55958

Observation 7cdaa740-39c3-46e1-a9ba-71ada3e1e97f · outbound

This paper cites Chatdev: Communicative agents for software development,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Chatdev: Communicative agents for software development,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:27.445450Z

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=2026-08-07T11:03:26.666148Z digest=sha256:3da4c6bf2a5535d7e058a03b5be3727729bab24eb062c295461130cd5cde360d

Observation beeff5fb-158c-414d-b03d-6ab7f8653833 · outbound

This paper cites Metagpt: Meta programming for a multi-agent collaborative framework,.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Metagpt: Meta programming for a multi-agent collaborative framework,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:03:27.265795Z

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=2026-08-07T11:03:26.732054Z digest=sha256:e922b14c6ec2c69ea049772580e9124353bd59cc4af8eeb266b6e0ef3ef00d9e

Observation 5fd4d2b4-876b-4e04-b989-39b90062f41b · outbound

This paper cites Exploration of LLM Multi-Agent Application Implementation Based on LangGraph+CrewAI.

SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization Exploration of LLM Multi-Agent Application Implementation Based on LangGraph+CrewAI

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T11:03:26.839202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:03:26.839202Z digest=sha256:1de9d682ab37f85e444f990f41225fba8b434e0b7da9069b4341d542767c151c

Pith citing papers

Observation 7bfb5752-a84c-4ba0-9578-6ff99145e599 · inbound

TrafficClaw: A Generalizable LLM Agent in the Unified Physical Environment for Urban Traffic Control cites this paper.

TrafficClaw: A Generalizable LLM Agent in the Unified Physical Environment for Urban Traffic Control SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:51:10.173761Z

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=2026-05-10T05:47:45.651391Z digest=sha256:a3ebea464a0620473bf7dc8b481da048fd2328aee6682608ce24ddbf6bd8076a

Observation 63157a14-d13b-4ec3-b6ab-68dff200d72b · inbound

Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO cites this paper.

Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:33:30.386617Z

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=2026-06-29T14:32:54.466546Z digest=sha256:606e30b80313d8137f13d132ca0f1e8c5591281fcf083919ab7eab5768fe5afe