TaaSchen

Driver training and competency development supported by telematics, video and AI

TaaSchen is the public umbrella for Hodos Media’s driver-training R&D. The programme examines how telematics, video and structured review can help instructors identify relevant driving events, discuss behaviour with drivers and build evidence of competency over time. The technology supports instructor judgement rather than replacing it.

Programme focus

TaaSchen covers telematics events, video capture, event-to-video linking, journey review, instructor and driver workflows, pre-brief and post-brief activity, competency evidence, data protection, consent, retention and responsible use of driver data. AI and machine learning are used where they can support prioritisation, analysis or structured review.

Technical questions

  • How can telematics events be linked reliably to the relevant video and journey context?
  • Which events and evidence are useful to instructors rather than merely available from the hardware?
  • How should AI summaries, confidence and data fusion be presented so that an instructor can review them critically?
  • What data-protection, consent and retention controls are required for practical training use?
  • How can progress be represented as competency development rather than a simple driver score?

Project sequence

AIPTO

2023-2024

Examined the feasibility of applying AI and machine learning to telematics data for more targeted driver feedback.

FAIDA

2024-2025

Developed and tested event-to-video integration and an instructor-led review workflow through a limited proof of concept.

FleetSkillAI

2025-2026

Extended the work into AI-supported competency development and an operational deployment with a training provider.

Programme outputs

Outputs include stakeholder and user requirements, system architectures, telematics and video integration methods, instructor workflow designs, data-protection analysis, user-interface concepts, operational trial evidence and exploitation planning. The accumulated methods, interfaces and integration knowledge form the current TaaSchen portfolio.