Pith Number

pith:TV3MTJPQ

pith:2026:TV3MTJPQ2NNZW74JDCJCDN6KGD

not attested not anchored not stored refs resolved

Emergency Vehicle Preemption Strategies using Machine Learning to Optimize Traffic Operations

Abhilasha Saroj, Angshuman Guin, Michael Hunter, Somdut Roy

A machine learning model decides when to preempt traffic signals for emergency vehicles to cut side delays while keeping response times near optimal.

arxiv:2605.13814 v1 · 2026-05-13 · cs.CE

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\usepackage{pith}
\pithnumber{TV3MTJPQ2NNZW74JDCJCDN6KGD}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Results demonstrate that the proposed algorithm can produce near-optimal ERV travel times while minimizing impacts on conflicting traffic.

C2weakest assumption

The calibrated microscopic simulation in PTV Vissim accurately captures real-world traffic dynamics and that ML models trained on its generated data will generalize to actual sensor inputs and field conditions.

C3one line summary

Machine learning models trained on traffic simulations can set emergency vehicle preemption times across multiple intersections to keep emergency response near optimal while cutting delays for conflicting traffic movements.

References

41 extracted · 41 resolved · 0 Pith anchors

[1] Connected Vehicle Pilot Deployment Program, 2021

[2] The Region’s Connected Vehicle Technology is Getting Ready to Roll, 2021

[3] Strategies to mitigate emergency department crowding and its impact on cardiovascular patients, 2023

[4] The impact of pre-hospital emergency care on outcome in patients with acute coronary syndrome; Clinical Medical Sciences -Research Proposal, 2013

[5] C. V. R. I. Architecture. "Emergency Vehicle Preemption," Feb 10, 2022; https://local.iteris.com/cvria/html/applications/app24.html#:~:text=Historically%2C%20priority%20for%20emergency %20vehicles,can 2022

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T02:44:15.359704Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

9d76c9a5f0d35b9b7f89189221b7ca30cb1fc9cf2d68762c85b8a67b7e5b6d22

Aliases

arxiv: 2605.13814 · arxiv_version: 2605.13814v1 · doi: 10.48550/arxiv.2605.13814 · pith_short_12: TV3MTJPQ2NNZ · pith_short_16: TV3MTJPQ2NNZW74J · pith_short_8: TV3MTJPQ

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/TV3MTJPQ2NNZW74JDCJCDN6KGD \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 9d76c9a5f0d35b9b7f89189221b7ca30cb1fc9cf2d68762c85b8a67b7e5b6d22

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "79188e8a2989befefb848c3e3c88d4f544df339d028b820672ac3ffe68ad9934",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CE",
    "submitted_at": "2026-05-13T17:41:27Z",
    "title_canon_sha256": "01af0004f81882ddf6dae890a00f6eeb8b323354a2e27a1b38fdd349747f8c10"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13814",
    "kind": "arxiv",
    "version": 1
  }
}