Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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.

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.

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.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.