2:40 pm - September 2, 2025
Dubai’s RTA, working with Yunex Traffic and Scientechnic, is rolling out Yutraffic FUSION and a UTC‑UX Fusion stack to create a live, simulation-driven model of its transport network aimed at cutting congestion and improving priority for public and emergency vehicles by mid-2026.
Dubai is rolling out a city-wide traffic management upgrade that centers on a real-time digital twin of its transport network, part of a broader push to make the emirate one of the world’s most data-driven smart cities. According to Robotics & Automation, this deployment marks the first use of Yunex Traffic’s Yutraffic FUSION platform in the Middle East and is being delivered in partnership with local systems integrator Scientechnic and Dubai’s Roads and Transport Authority (RTA).
At its heart, the program builds a dynamic, ever-updating model of Dubai’s road and multimodal network. It ingests historical traffic patterns, live sensor feeds, and other telemetry to simulate short-term scenarios and forecast flows. The system can automatically optimize signal timings, test the likely impact of planned changes via simulation, and prioritize movements for buses, trams, cyclists, and pedestrians. The platform is also designed to support cooperative intelligent transport systems (C-ITS/V2X), connected vehicles, and future autonomous operations, according to RTA statements and vendor material.
The RTA has framed the upgrade around its next-generation UTC-UX Fusion stack, which combines artificial intelligence and predictive analytics with the digital twin environment. The authority says the program will be installed across major intersections and aims to be substantially complete in the first half of 2026. Officials have projected roughly 10–20% improvements in intersection congestion and journey times as a result of dynamic optimization and better incident response.
Dubai’s rationale is clear. The city’s transport network moves very large numbers of people: RTA figures show public transport, shared mobility, and taxis carried 747.1 million riders in 2024, up from 702 million in 2023, with average daily ridership above two million. The Robotics & Automation coverage also notes that Dubai handles more than three million vehicles during peak hours on its busiest corridors, creating a strong business case for simulation-led control to cut delays and emissions while boosting reliability.
The choice of Yutraffic FUSION aligns with recent European deployments that Yunex and partners cite as proof of concept. Transport for London’s shift to a cloud-hosted real-time optimiser and UTC‑UX platform—delivered with Yunex Traffic—has been described by TfL and industry partners as improving journey times, bus priority, and incident response, and as forming the technical backbone for adaptive control. Industry summaries and ERTICO briefings indicate that digital-twin and Fusion-enabled systems in cities such as London have delivered travel-time reductions of up to around 20% in some corridors, along with fewer stops and lower emissions where prioritization policies are applied.
Locally, Scientechnic’s involvement reflects its long-standing role as Dubai’s systems integrator for traffic signaling and intelligent transport systems. The company’s project materials outline prior work supplying, installing, and commissioning SCOOT/PC-SCOOT servers and UTC systems in the emirate and position it to manage migration, integration, and ongoing maintenance for the upgrade.
While the new stack promises adaptive, policy-driven control and the ability to simulate ‘what-if’ scenarios before they go live, municipal and vendor projections remain projections. The RTA’s 10–20% improvement range and vendor claims of emissions reductions are reasonable and in line with other implementations, but actual outcomes will hinge on local factors such as data quality, sensor coverage, the pace of rollout across congested corridors, and integration with public-transport priority and enforcement measures. Officials have signaled that prioritizing emergency and public transport movements will be an early focus as intersections come online.
If the program hits its timetable and targets, Dubai will be adding a centralized simulation and optimization layer to a transport network that already sees growing use of public transit. That could give planners a stronger toolkit to manage peak demand, test infrastructural changes virtually before committing to physical works, and align traffic control with the emirate’s environmental and mobility goals.
For now, the claim is that Dubai is moving from static signal timing to a continuously adaptive, data-driven model of traffic control. The coming months—and the scheduled completion window in the first half of 2026—will reveal whether the digital twin can deliver the operational and environmental gains that the RTA and its partners say are possible.
Source: Noah Wire Services
- https://www.roboticsandautomationmagazine.co.uk/news/infrastructure/dubai-deploys-digital-twin-traffic-technology-in-major-smart-city-initiative.html – Please view link – unable to able to access data
- https://www.roboticsandautomationmagazine.co.uk/news/infrastructure/dubai-deploys-digital-twin-traffic-technology-in-major-smart-city-initiative.html – Robotics & Automation reports that Dubai has started deploying a digital twin‑based traffic management platform, becoming the first Middle East city to adopt Yutraffic FUSION. The article explains the system creates a real‑time, dynamic digital twin of Dubai’s transport network using live sensors and historical data to simulate scenarios, optimise signal timings and manage multimodal flows. It notes the rollout targets key congestion hotspots via a partnership involving Yunex Traffic, local distributor Scientechnic and Dubai’s RTA. The piece highlights objectives to improve efficiency, cut emissions, support connected vehicles and prepare for autonomous transport, referencing similar London projects as inspiration nationwide.
- https://www.rta.ae/wps/portal/rta/ae/home/news-and-media/all-news/NewsDetails/launching-traffic-signal-control-system-upgrade-using-ai-and-digital-twin-technology – The Roads and Transport Authority (RTA) announced the upgrade of Dubai’s traffic signal control system to the next‑generation UTC‑UX Fusion, integrating artificial intelligence, predictive analytics and digital twin technology. The RTA stated the programme will be deployed across major intersections and is expected to complete by the first half of 2026. Officials highlighted benefits including dynamic optimisation of signal timings, simulation of changes using a digital twin, and prioritisation for public transport and emergency vehicles. The RTA also confirmed the system will support Cooperative Intelligent Transport Systems (C‑ITS/V2X). Projected improvements include a 10–20% reduction in intersection congestion and journey times.
- https://www.wired-gov.net/wg/news.nsf/articles/TfL%2Band%2BYunex%2Bsuccessfully%2Bcomplete%2Bworld%2Bleading%2Bupgrade%2Bto%2BLondons%2Btraffic%2Bsignal%2Bsystem%2B10062024121500 – A media report reproducing the Transport for London announcement describes the migration to a cloud‑hosted Real Time Optimiser (RTO) and UTC‑UX platform delivered with Yunex Traffic across London’s signal network. The release explains the system operates thousands of junctions and SCOOT links, adds new user interfaces and bus priority functions, and forms the backbone for deploying Fusion adaptive control. TfL said the upgrade will improve journey times, traffic flows and incident response, support healthier travel choices and air quality aims, and provide richer data to modernise and future‑proof the capital’s traffic control capabilities.
- https://erticonetwork.com/state-of-baden-wurttemberg-launches-yutraffic-fusion-by-yunex-traffic/ – An ERTICO news item outlines local deployments of Yutraffic FUSION and describes how the system models traffic in real time by combining live and historical data to predict short‑term traffic and automatically adjust signal timings. The piece cites results from prior implementations — referencing London — where digital twin and Fusion‑enabled controls reportedly reduced travel times by up to 20% and decreased stops, while enabling multimodal and policy‑driven prioritisation for buses, trams, cyclists and pedestrians. The article positions FUSION as an AI‑enabled optimiser that lowers delays and emissions across diverse urban corridors.
- https://www.scientechnic.com/projects/urban-traffic-control-dubai/ – Scientechnic’s project page describes the company’s involvement in Dubai’s Urban Traffic Control works, detailing supply, installation, testing and commissioning of PC‑SCOOT servers and UTC systems. The page highlights Scientechnic’s role in migration and upgrade projects for Dubai traffic management, plus maintenance contracts and ITS implementations for high‑profile areas. It demonstrates the firm’s long experience as a local systems integrator and distributor capable of delivering complex traffic signalling, control and monitoring projects — evidencing the presence of regional partners able to support advanced ITS and digital twin deployments in Dubai’s mobility ecosystem.
- https://www.rta.ae/wps/portal/rta/ae/home/news-and-media/all-news/NewsDetails/747-million-riders-used-public-transport-shared-mobility-and-taxis-in-2024 – The Roads and Transport Authority reported that public transport, shared mobility and taxis carried 747.1 million riders in 2024, up from 702 million in 2023, with average daily ridership exceeding two million. The release breaks down mode shares and specific figures for metro, buses, trams, marine transport, shared mobility and taxis, and highlights growth in shared mobility and public transport use. RTA framed these results as evidence of increased public transport adoption and as justification for continued investment in infrastructure and smart mobility tools intended to improve capacity, sustainability and reduce reliance on private vehicles and journey delays.
Noah Fact Check Pro
The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The narrative was published on August 15, 2025, and aligns with Dubai’s ongoing initiatives to integrate digital twin technology into traffic management. Similar reports appeared in February 2025, indicating that the core information is not new. However, the specific mention of the Yutraffic FUSION platform and the partnership with Scientechnic and RTA adds new details, justifying a higher freshness score. The report appears to be based on a press release, which typically warrants a high freshness score. No significant discrepancies in figures, dates, or quotes were found. The narrative does not appear to be recycled across low-quality sites or clickbait networks. The update may justify a higher freshness score but should still be flagged.
Quotes check
Score:
9
Notes:
The report includes direct quotes from Hussain Al Banna, CEO of RTA’s Traffic and Roads Agency. These quotes appear to be original and have not been identified in earlier material. No identical quotes were found in earlier reports, indicating potential originality.
Source reliability
Score:
7
Notes:
The narrative originates from Robotics and Automation Magazine, a specialised publication focusing on robotics and automation. While it is a niche source, it appears to be reputable within its field. The report cites official statements from RTA and mentions partnerships with established entities like Scientechnic, lending credibility to the information. However, the reliance on a press release without additional independent verification slightly lowers the reliability score.
Plausability check
Score:
8
Notes:
The claims about Dubai’s adoption of digital twin technology for traffic management are plausible and align with the city’s previous initiatives in smart city development. The integration of AI, predictive analytics, and digital twin technologies into traffic signal control systems has been reported by other reputable outlets. The specific details about the Yutraffic FUSION platform and the partnership with Scientechnic are new and have not been covered elsewhere, which adds credibility to the report. The language and tone are consistent with official communications from RTA, and there are no signs of excessive or off-topic detail.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): HIGH
Summary:
The narrative provides new details about Dubai’s adoption of the Yutraffic FUSION platform for traffic management, supported by direct quotes from RTA officials and consistent with the city’s ongoing smart city initiatives. The source is reputable within its niche, and the claims are plausible and align with previous reports. No significant issues were identified, leading to a high confidence in the overall assessment.
