Paper Citation Record · LEDGER

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2501.16728.

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

pith.paper-citation-record.v1
2501.16728 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:10:44.963091Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

34 of 34 outbound references displayed

verified exact1
verified fuzzy26
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 24983991-fc06-4ccc-9ac8-d5abe13e5184 · outbound

This paper cites Neural network vehicle models for high-performance automated driving,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Neural network vehicle models for high-performance automated driving,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b98fca6d-196e-4283-8cc9-4c1172de702d · outbound

This paper cites Using online verification to prevent autonomous vehicles from causing accidents,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Using online verification to prevent autonomous vehicles from causing accidents,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T11:10:44.757840Z

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Observation 26130430-e821-46d6-872f-8ffd55fe3e5f · outbound

This paper cites Dense reinforcement learning for safety validation of autonomous vehicles,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Dense reinforcement learning for safety validation of autonomous vehicles,

Reference 3

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Observation 93714c08-974e-4f57-ba4b-7f1ad980b510 · outbound

This paper cites Reinforcement learning for mixed autonomy in- tersections,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Reinforcement learning for mixed autonomy in- tersections,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.799686Z

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Observation a369dced-22cf-45da-ab92-4f86c9858060 · outbound

This paper cites Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections

Reference 5

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Observation d3863d1b-2a01-48c3-bf59-12e49f30a4ac · outbound

This paper cites Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.767548Z

Source-reported events for the cited work

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Observation 71841976-d1a8-4ce1-a035-026e71af153e · outbound

This paper cites Flow: A modular learning framework for mixed autonomy traffic,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Flow: A modular learning framework for mixed autonomy traffic,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.747686Z

Source-reported events for the cited work

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Observation 2544a05a-39f3-4ed9-aa94-890d939dedad · outbound

This paper cites A survey on intelligent traffic lights,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark A survey on intelligent traffic lights,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.721260Z

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Observation d25d7a10-4f8d-4e56-a42e-373fd228b6e9 · outbound

This paper cites A Survey on Traffic Signal Control Methods.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark A Survey on Traffic Signal Control Methods

Reference 9

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Observation fff7b766-cfcf-4563-870a-4d5ec1e457df · outbound

This paper cites Traffic light control design approaches: a systematic literature review.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Traffic light control design approaches: a systematic literature review

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.699273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b7f03947-bdb1-44cc-b674-0622d7628a4d · outbound

This paper cites A protocol for mixed autonomous and human-operated vehicles at intersections,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark A protocol for mixed autonomous and human-operated vehicles at intersections,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.674696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7c165577-7542-4073-bedc-d2b1a343a9c6 · outbound

This paper cites Polling-systems-based autonomous vehicle coordination in traffic intersections with no traffic signals,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Polling-systems-based autonomous vehicle coordination in traffic intersections with no traffic signals,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.651932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8c4859e0-7115-4b74-b74d-e288a6411e2c · outbound

This paper cites Controllability analysis and optimal controller synthesis of mixed traffic systems,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Controllability analysis and optimal controller synthesis of mixed traffic systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.631904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 257285b7-e6f9-49d8-aa7f-9e92d80aa97c · outbound

This paper cites Coop- erative merging control via trajectory optimization in mixed vehicular traffic,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Coop- erative merging control via trajectory optimization in mixed vehicular traffic,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.608475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2d8a360d-eb18-48ec-8c84-9d81157b02c3 · outbound

This paper cites Summit: A simulator for urban driving in massive mixed traffic,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Summit: A simulator for urban driving in massive mixed traffic,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.584410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1a3977f3-4fbc-4e0a-a714-3f2f987aaf2e · outbound

This paper cites Towards a systematic computational framework for modeling multi-agent decision-making at micro level for smart vehicles in a smart world,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Towards a systematic computational framework for modeling multi-agent decision-making at micro level for smart vehicles in a smart world,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.556651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f3ee0854-7024-4384-b8f2-32b985bb3cb6 · outbound

This paper cites A general approach to smoothing nonlinear mixed traffic via control of autonomous vehicles,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark A general approach to smoothing nonlinear mixed traffic via control of autonomous vehicles,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.533129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 57bdca24-7378-413a-9c5a-228e1e5e9596 · outbound

This paper cites Cooperative driving in mixed traffic of manned and unmanned vehicles based on human driving behavior understanding,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Cooperative driving in mixed traffic of manned and unmanned vehicles based on human driving behavior understanding,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.499631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8c468511-ad51-4e2d-9174-48bf74741fef · outbound

This paper cites Cooperation for scalable supervision of autonomy in mixed traffic,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Cooperation for scalable supervision of autonomy in mixed traffic,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.471698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dfdd0444-64cd-4c64-b8e4-a6eb3ee1ae60 · outbound

This paper cites A survey on urban traffic control under mixed traffic environment with connected automated vehicles,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark A survey on urban traffic control under mixed traffic environment with connected automated vehicles,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.451796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 423396f6-0b66-4367-8988-ea7250dc2e16 · outbound

This paper cites Courteous behavior of automated vehicles at unsignalized intersections via re- inforcement learning,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Courteous behavior of automated vehicles at unsignalized intersections via re- inforcement learning,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e46e6061-e186-4679-9ec9-256692fdd71b · outbound

This paper cites La- grangian control through deep-rl: Applications to bottleneck deconges- tion,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark La- grangian control through deep-rl: Applications to bottleneck deconges- tion,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.397474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a446b2a5-f4ca-4470-a286-a95615959b41 · outbound

This paper cites Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.366553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fdb23fa9-db8e-450e-8784-6389db065589 · outbound

This paper cites Mixed-autonomy traffic control with proximal policy optimization,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Mixed-autonomy traffic control with proximal policy optimization,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.338791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5e6c3d0d-d46d-4179-a4d0-437103c98131 · outbound

This paper cites Hybrid traffic control and coordination from pixels,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Hybrid traffic control and coordination from pixels,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.317853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 876244a0-6329-4f0c-93a1-4e5aa77f8ebd · outbound

This paper cites Analyzing emissions and energy efficiency in mixed traffic control at unsignalized intersections,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Analyzing emissions and energy efficiency in mixed traffic control at unsignalized intersections,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.289819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cfb3658e-fa4e-4eae-bf4c-5f95f586f3ef · outbound

This paper cites Large-scale mixed traffic control using dynamic vehicle routing and privacy-preserving crowdsourcing,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Large-scale mixed traffic control using dynamic vehicle routing and privacy-preserving crowdsourcing,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.269857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 08e30443-80bc-401b-8c54-66998d800634 · outbound

This paper cites Multi- objective optimal control for proactive decision making with temporal logic models,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Multi- objective optimal control for proactive decision making with temporal logic models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.244308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ee66d90d-3814-45e0-9fce-cb7467d8fba5 · outbound

This paper cites Rainbow: Combining improvements in deep reinforcement learning,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Rainbow: Combining improvements in deep reinforcement learning,

Reference 29

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Source-reported events for the cited work

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Observation 4e78ad1a-31ed-44ee-8487-208e809f1b19 · outbound

This paper cites Discrete and Continuous Action Representation for Practical RL in Video Games.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T11:10:44.935982Z

Source-reported events for the cited work

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Observation 746f6bda-427e-43b1-94c5-092909318637 · outbound

This paper cites Sumo’s lane-changing model,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Sumo’s lane-changing model,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.210273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a28f4b8c-656f-4abb-87f1-f3d3b82bf3a2 · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T11:10:44.951927Z

Source-reported events for the cited work

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Observation a12f72b2-eba2-4179-8082-0dd555f13129 · outbound

This paper cites Sumo– simulation of urban mobility: an overview,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Sumo– simulation of urban mobility: an overview,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.166264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e62198f3-87be-413e-8363-5582f5c5f4de · outbound

This paper cites Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity,.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:10:45.141523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

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