In training, as in all areas, data allows us to learn more about our good and bad habits, our strengths and weaknesses. It allows us to evaluate, measure and personalise learning for the benefit of both the trainer and the learner, provided that the right indicators are identified.
The trainer's eye: an essential assessment tool
In real-life situations, observation is the trainer’s main tool: it is up to them to check that each manoeuvre is performed correctly and on time. Most trainers use a qualitative grid or a score: they give a mark for the learner’s skills. The aim is to be able to give them feedback and offer them retraining focused on their weaknesses.
To support this observation, trainers equipped vehicles with telematics boxes and applications to measure sudden acceleration, emergency braking, and speed compliance.
From collection to performance indicators
Of course, observation alone is not always enough to measure progress or correct automatic behaviours. Far from replacing human analysis, data collection complements it. It provides measurable, usable and comparable benchmarks over time, which are essential for establishing good behaviours in the long term.
In a simulator driving session, several key indicators are used to assess a learner’s progress. Among the most frequently monitored are:
- Reaction time: ability to detect danger and act.
- Maintaining safe distances: in metres or seconds.
- Frequency and intensity of emergency braking.
- Using indicators and checking blind spots.
- Compliance with speed limits.
- Smooth manoeuvring: hill starts, merging onto motorways, managing priorities.
- Critical errors: crossing a solid line, running a red light, failing to give way.
These elements, among others, enable the trainer to objectively assess the driver’s aptitude, but also to justify, in a fully transparent manner, the progress made or the areas that need further work.
The advanced features of the simulator
Driving simulators provide a controlled environment in which this data is not only collected in real time, but can also be used through powerful educational tools. Far from replacing learning in real-life conditions, they enrich it.
For example, replay allows you to replay a situation that occurred a few minutes earlier and analyse the driver’s decision-making together. Eye tracking allows you to identify cognitive blind spots: areas overlooked during visual scanning, failure to check road signs or rear-view mirrors.
At the end of the session, an individualised assessment is automatically generated: it summarises the key indicators, highlights areas for improvement, and suggests appropriate learning progression. This objective feedback is a powerful tool for learners: they can see their mistakes, understand what needs to be improved, and track their progress from one session to the next.
Each vehicle has its own indicators
A lorry driver, bus driver or car driver do not face the same constraints. Performance indicators must therefore be tailored to each type of vehicle and task.
For example:
- In passenger transport (coach, bus): KPIs often focus on passenger comfort (sudden braking, sharp turns), stop management and route regularity.
- When driving goods vehicles: the focus is on controlling the vehicle’s dimensions, fuel consumption (in relation to eco-driving) and compliance with the tachograph.
- In basic training (B licence): priority is given to safety reflexes and anticipation in urban environments.
Simulators allow scenarios to be customised according to these contexts. They are also capable of incorporating specific constraints: night driving, difficult weather conditions, the presence of vulnerable road users, or even simulated incidents (engine failure, emergency braking, etc.).
This enables trainers to choose the right indicators, reproduce the right contexts, and provide tailored support. Data is not an end in itself, but rather a lever for more effective, equitable, and secure training.