Scoot 8 AI is latest version of TRL’s UTC solution
TRL Software has unveiled Scoot 8 AI, the newest iteration of its long-standing, hardware-agnostic urban traffic control (UTC) platform. Building on a brand approaching its 50th year, the release introduces predictive artificial intelligence designed to forecast traffic conditions up to 30 minutes ahead—aiming to shift traffic management from reactive to proactive.
TRL positions Scoot 8 AI as a step-change for city operations, promising journey-time reductions of up to 15% compared with current-generation systems, with even larger improvements for authorities upgrading from earlier versions of Scoot. The company also highlights a “typical ROI within 12 months,” supported by real-time performance measurement.
From adaptive to predictive
The core update in Scoot 8 AI centers on predictive control. By forecasting network demand and adjusting signal timings in advance, the system targets smoother flow, shorter delays, and quicker response to incidents. TRL says the embedded algorithms reduce the need for manual interventions, enabling operators to focus on strategy and exception handling rather than routine adjustments.
“By combining our proven adaptive control with predictive AI, we are not just responding to congestion, we are preventing it. More importantly, we are tracking every outcome to give cities real confidence that their investment is delivering tangible results on their streets,” said Christopher Kettell, chief technologist at TRL Software.
Faster incident detection
Alongside the predictive engine, Scoot 8 AI introduces anomaly detection intended to spot unusual patterns across the network. According to TRL, this can identify incidents up to 40% faster—often before emergency calls are made—helping agencies mobilize resources earlier and minimize knock-on delays.
Measuring ROI in real time
To back up performance claims, TRL has integrated real-time dashboards that track outcomes and return on investment. These tools are designed to give traffic teams a clearer view of the impact on journey times, delays, and reliability, while supporting transparent reporting to city stakeholders.
Openness and integration
True to its hardware-agnostic heritage, Scoot 8 AI is built to work across diverse roadside equipment and control room environments. TRL notes that the platform can integrate with third-party services, including Waze for Cities, enabling data exchange that can enhance network awareness and traveler information.
Why it matters for cities
- Proactive management: Forecasting traffic up to 30 minutes ahead aims to prevent rather than simply mitigate congestion.
- Operational efficiency: Reduced manual interventions free up staff capacity for higher-value tasks.
- Incident response: Earlier detection can contain disruption and improve safety outcomes.
- Performance transparency: Built-in dashboards help quantify benefits and support investment cases.
- Incremental gains: Cities running older Scoot versions may see larger improvements when upgrading, according to TRL.
As urban networks grapple with rising demand and constrained road space, TRL is pitching Scoot 8 AI as a modernized UTC platform that blends decades of adaptive control experience with predictive analytics. While the performance figures are the company’s own, the emphasis on measurable outcomes—and the promise of a typical 12‑month payback—will likely resonate with authorities seeking both congestion relief and clear evidence of return.
