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Integrated System for driver TRaining and Assessment using Interactive education tools and New training curricula for ALL modes of road transport

TRAIN-ALL aims to develop a computer-based training system for the training and assessment of different land-based driver cohorts (motorcycle riders, novices, emergency drivers and truck drivers) that integrates multimedia software, driving simulator, virtual driving simulator and onboard vehicle sensors into a single modular platform.

Tags: Road


Over 80% of all traffic accidents can be directly attributed to the human factor so emphasis must be given to driver operator training. Traffic participants range from car and motorcycle to truck drivers and all need to be trained in a specific way. Indicatively:

  • novice drivers of passenger cars have no possibility of enhancing risk awareness and need training in other higher order skills.
  • motorcycle drivers have no experience on using safety equipment and low experience on driving different types of motorcycles.
  • heavy vehicle drivers get most of their experience on the road and are often involved in specific accident types.
  • drivers of emergency vehicles only get a few possibilities to practise on the complexities of interaction with other traffic participants.

There is a pan-European consensus on the fact that driver training needs to expand away from its current focus on controlling the vehicle in traffic, so as to cover ‘higher level’ strategic factors. TRAIN-ALL will improve initial and continuous driving training in order to stimulate road users towards a more responsible behaviour. In this way the project will contribute to the European Road Safety Action Programme’s goal of halving the number of road fatalities in 2010.


The main objectives are to:

  • prioritise a set of training scenarios for each driver type
  • develop a common and concise ontological framework for computer-based training (CBT) tools, functionalities and scenarios
  • develop a cost-efficient and valid methodology to assess simulator reliability and fidelity
  • employ intelligent agent technology in order to develop CBT with AmI-based traffic participants
  • develop co-operative training scheme and co-driver training (for emergency vehicle co-pilots) scenarios and tools
  • develop the appropriate P2P tools to allow CBT networking and even real-time collaboration
  • develop a virtual instructor module that will allow autonomous and cost-effective multi-user training by CBT.
  • develop and test the method of adaptive training
  • develop appropriate training schemes and scenarios for CBT in the use of new driver assistance and information systems
  • use an existing motorcycle simulator and adapt it accordingly
  • develop cost-effective, high fidelity, low dizziness and modular driving simulator tools for passenger cars and trucks, and a virtual driving simulator for passenger cars
  • develop new, improved training and assessment curricula for drivers
  • evaluate the viability, usability and usefulness of the developed tools and curricula in ten pilots
  • estimate the potential road safety enhancement due to the developed tools and curricula
  • produce detailed exploitation and business plans for the developed tools.
The TRAIN-ALL cube: target groups in relation to the training media and the training dimensions that are considered within the project
The TRAIN-ALL cube: target groups in relation to the training media and the training dimensions that are considered within the project

Description of work

Work starts with benchmarking and classification activities on CBT tools and curricula for driver training and assessment, to lead to a common CBT and assessment model and prioritisation of training requirements.

The development encompasses building a common system architecture for distributed interoperable driving simulators (ontology-based), and a knowledge management tool to collect and process centrally the trainee performance data from different simulators, as well as a simulator validity assessment methodology.

Enabling technologies will be built, including an ambient intelligence framework, co-operative driving and group training module, an immersive simulation platform for virtual reality (VR)-based training, CBT tools connecting internet network supporting scenario sharing, a virtual instructor and debriefing module, simulation sickness aversion principles and guidelines, enhanced reality and adaptive training module.

The new modules are integrated into different simulator prototypes (motorcycle, passenger car, truck, immersive (VR) simulator and modular/integrated driving simulator).

Developed prototypes will be tested in ten pilots, leading to an impact analysis on the usefulness and value of the use of driving simulators for driver training and assessment.

An information dissemination framework, cost benefit analysis, cost effectiveness analysis and exploitation plans, application guidelines, proposals towards adequate standards, CBT-based training and assessment certification and accreditation schemes complement the work plan.


Key Deliverables:

D1.1 Benchmarking and classification of CBT tools for driver training

D1.2 Training needs and scenario definition

D2.1 Common system architecture for driving simulators based on interoperable federates

D2.2 Knowledge management tool

D2.3 Driving simulator functional validity assessment methodology

D3.1 Ambient intelligence module

D3.2 Co-driving, co-operative and group training modules

D3.3 Immersive simulation platform

D3.4 i3-based tool for networked learning and remote control of simulators

D3.5 Virtual instructor and debriefing modules

D3.6 Dynamic scenario management module

D3.7 ADAS/IVICS simulation module

D3.10 Enhanced reality module

D3.11 Module for controlling adaptive training sequences

D4.1 Adapted motorcycle simulator prototype

D4.2 Adapted truck simulator prototype

D4.3 Adapted car simulator prototype for emergency vehicle drivers

D4.4 Adapted car simulator prototype for novice drivers

D4.5 Adapted VR simulator prototype

D4.6 Multi-purpose driving simulator prototype

D5.3 Proposal for an integrated training curriculum and impact analysis

D6.2 Demonstration pilot results consolidation

D7.3 Cost benefit and cost effectiveness analysis

D7.4 Exploitation and business plans

The CRF virtual reality driving simulator
The CRF virtual reality driving simulator