London Adaptive Traffic Signals (FUSION / Real Time Optimiser)
This overview was generated with AI from the public sources listed below and checked against them before publication. It has not had a complete human fact-check — treat it as a starting point and follow the sources.
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Since 2020 TfL and Yunex Traffic (formerly Siemens Mobility, with the University of Southampton) have been developing FUSION, an adaptive signal-control system meant to replace the 30-year-old SCOOT by drawing on richer multi-modal data, including connected-vehicle and bus feeds. In June 2024 TfL completed migrating almost 4,000 junctions and 1,500 pedestrian crossings onto the cloud-based Real Time Optimiser platform that will host it — some 5,500 of the roughly 6,400 signal sites it manages. FUSION itself is still running at a handful of 'living laboratory' trial junctions while SCOOT keeps controlling most of the capital. TfL's 2026 'London on the move' strategy projects up to 14% less delay and ~£1bn in benefits once FUSION progressively replaces SCOOT; AI-based enhancements are framed as a future upgrade, not a current capability.
what does this mean?
The strongest source is the operator's or the city's own reporting — an official report, dataset or press release. It grades who did the looking — not how well the project went. All four grades →Sources
Show your work What this page rests on and what it can’t tell you · all 8 claims with their sources · the forensic record
Evidence Passport · public beta 8 addressable claims, 4 source dossiers, one permanent baseline. The passport is unreviewed — an AI-assisted structural migration, not a human or expert endorsement. Every revision keeps a permanent copy under revision history.
Inspect the claims, one by one — verbatim text, sources and caveats for all 8
The text below is copied verbatim from the published record. Each claim names the source dossiers that carry it; caveats stay attached to the claim they qualify.
clm-5ba8a2c0087040d7
quantitative
Since 2020 TfL and Yunex Traffic (formerly Siemens Mobility, with the University of Southampton) have been developing FUSION
Sources carrying this claim
clm-22cd9e7c237b6f96
quantitative
an adaptive signal-control system meant to replace the 30-year-old SCOOT
Sources carrying this claim
clm-66e0e68587362ce7
descriptive
by drawing on richer multi-modal data, including connected-vehicle and bus feeds
Sources carrying this claim
clm-630c80e1eb2faeaa
quantitative
In June 2024 TfL completed migrating almost 4,000 junctions and 1,500 pedestrian crossings onto the cloud-based Real Time Optimiser platform that will host it
Sources carrying this claim
clm-fbd7c0132591e879
descriptive
FUSION itself is still running at a handful of 'living laboratory' trial junctions
Sources carrying this claim
clm-01764ff84cf8e792
descriptive
while SCOOT keeps controlling most of the capital
Sources carrying this claim
clm-fa48d0d66267f607
quantitative
TfL's 2026 'London on the move' strategy projects up to 14% less delay and ~£1bn in benefits once FUSION progressively replaces SCOOT
Sources carrying this claim
clm-4c0e0c533d56c756
descriptive
AI-based enhancements are framed as a future upgrade, not a current capability
Sources carrying this claim
Forensic record — source dossiers, gaps, hashes and the exact revision this page renders
This layer records what is known about each source, what is still missing, and the exact snapshot this page is rendering. A missing date, archive or hash stays visible as missing.
Awaiting operator and domain-expert review; publication of this revision implies neither.
sha256:8aee675f5d3dcc292cdc846e8eefda4c7b4bd06f432e5cbfae435ed07867cc42
- 8
- of 8 claims mapped
- 4
- source dossiers
- 4
- publication dates recorded
- 0
- archives linked
- 0
- exact locators
- 0
- content captures hashed
Governance facts carried by the record
- Operator
- Transport for London (Yunex Traffic vendor)
- Actor types
- utility, private
- Funding model
- public
- Funding description
- Not recorded
- Cost
- Not recorded
- Ownership
- Not recorded
- Decision rights
- Not recorded
- Exit conditions
- Not recorded
4 source dossiers
TfL / Yunex Traffic press release, 'TfL and Yunex successfully complete world-leading upgrade to London's traffic signal system', 10 June 2024
- Stable source ID
src-8b9d709534927e8c- Publisher
- Name not classified · wired-gov.net
- Type / language
- web-page · language not classified
- Published
- 2024-06-10
- Updated
- Not recorded
- Source last checked
- No source-level check date
- Record last verified
- 2026-08-06
- Dossier created
- 2026-08-22
- Retrieved copy
- No local capture recorded
- Archive
- No archived copy linked
- Content hash
- No captured content hash
- Locator
- Descriptive only — not page/paragraph exact
Open the recorded source note
Confirms June 2024 completion of the cloud RTO migration: ~6,400 signal sites, ~4,000 junctions, 1,500 crossings, 16,000+ detectors; FUSION to replace SCOOT
- Claims linked
Yunex Traffic newsroom, 'Urban Traffic Control solution live across London', 7 June 2024
- Stable source ID
src-7049d0840610bd57- Publisher
- Name not classified · yunextraffic.com
- Type / language
- web-page · language not classified
- Published
- 2024-06-07
- Updated
- Not recorded
- Source last checked
- No source-level check date
- Record last verified
- 2026-08-06
- Dossier created
- 2026-08-22
- Retrieved copy
- No local capture recorded
- Archive
- No archived copy linked
- Content hash
- No captured content hash
- Locator
- Descriptive only — not page/paragraph exact
Open the recorded source note
Confirms UTC-UX/RTO hosted platform live citywide (~5,500 junctions+crossings); FUSION deployment 'over the coming years' — i.e. platform complete, FUSION rollout ongoing
- Claims linked
Traffic Technology Today, 'Siemens Mobility and TfL announce launch of the new SCOOT' (Sitraffic FUSION, developed with University of Southampton)
- Stable source ID
src-4e0c171abfb7e6de- Publisher
- Name not classified · traffictechnologytoday.com
- Type / language
- web-page · language not classified
- Published
- 2020-09-24
- Updated
- Not recorded
- Source last checked
- No source-level check date
- Record last verified
- 2026-08-06
- Dossier created
- 2026-08-22
- Retrieved copy
- No local capture recorded
- Archive
- No archived copy linked
- Content hash
- No captured content hash
- Locator
- Descriptive only — not page/paragraph exact
Open the recorded source note
Confirms vendor (Siemens Mobility, now Yunex) + University of Southampton, FUSION entered operation Autumn 2020 at trial sites, uses connected-vehicle and bus data
TfL newsroom, 'TfL unveils ambitious five-year plan... London on the move', 26 Jan 2026
- Stable source ID
src-620ccd907f4f74aa- Publisher
- Name not classified · tfl-newsroom.prgloo.com
- Type / language
- web-page · language not classified
- Published
- 2026-01-26
- Updated
- Not recorded
- Source last checked
- No source-level check date
- Record last verified
- 2026-08-06
- Dossier created
- 2026-08-22
- Retrieved copy
- No local capture recorded
- Archive
- No archived copy linked
- Content hash
- No captured content hash
- Locator
- Descriptive only — not page/paragraph exact
Open the recorded source note
Source of the 'up to 14% less delay' and ~£1bn benefit projection; states FUSION 'can be upgraded in future to take advantage of artificial intelligence' — AI is a future phase; 3,500 figure = signals on bus routes, not total
- Claims linked
Known limits of this passport
- Publisher names and source languages have not yet been classified; domains are recorded without guessing.
- Existing source notes are descriptive locators, not page- or paragraph-exact citations.
- A missing archive, publication date or content hash is shown as null rather than inferred.
- The project-level evidence grade ranks the strongest source in the entry; it is not a truth score for every claim.
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📎 Cite this project
1001 Smart Cities (2026). “London Adaptive Traffic Signals (FUSION / Real Time Optimiser)” — London, United Kingdom. The Smart City Atlas. https://1001smartcities.org/projects/london-fusion-adaptive-signals/ (last verified 2026-08-06). Data: CC BY 4.0.
The underlying data is free to reuse with attribution — see the open data page.
