Benefit from our physics-based approach to leverage your driving data

We use the fundamental and universal laws governing vehicle dynamics and the energy consumed by the engine.

Collection and processing of driving data

Data source

We accurately measure the drive by analysing the essential variables describing a vehicle's movement.

Travel speed, acceleration, direction and rotational speed describe the dynamics of a vehicle. These quantities can be measured with a smartphone or with a telematics system.

What is the input data used for our algorithms?

We analyse time variables recorded at rate of one per second to capture the essential events related to a vehicle's movement.

Our services use speed, direction and elevation while accounting for the category, accuracy and quality of the measurement system in question. In the case of on-board systems, we also process all kinds of vehicle data types: engine rpm, steering wheel angle, battery voltage.

Finally, the technical characteristics of the vehicle are accounted for by our algorithms: mass, dimensions, engine, gearbox, etc.

Journey processing sequence

In order to manage heterogeneous data collection systems, we first identify the types of input data. They are analysed, corrected and supplemented if required, then resampled.

Our signal analysis and processing services quantify data to be measured and diagnose the telematics system or smartphone sensors.

All of our driving scores and indicators are based upon Control Theory, which consists of modelling a dynamic system as an equation while preserving the fundamental relationships which explain it.

Our web services and SDKs use the same algorithms as those entered into a vehicle's ECU by motorists and automotive engineers.

Olivier Grondin

Olivier Grondin

Product & Innovation Director - Co-founder

DriveQuant

The phenomena which take place when a vehicle moves, which we can all sense intuitively, or which statistics can attempt to model, are in fact governed by immutable physical laws.

Algorithms converting driving data
into services

Energy spending

We estimate the fuel consumption of tourism and utility vehicles in real driving conditions. These estimates are based upon physics: the real time tracking of values such as energy spending, fuel consumption and the CO2 emissions produced by the vehicle.

We analyse the effect of operating conditions, driver behaviour and the topography upon fuel consumption in great detail: operation when the engine is cool or idling, over or under-revving as a result of the selected gear, and consumption related to the slope of the road.

We reconstruct the mechanical traction strength using the speed and mass of the vehicle by taking an inverse approach. Power transfer is carried out across each component of the drive train in order to calculate the engine torque.

Finally, the torque and engine speed are used to calculate fuel mass based on mapping engine consumption.

Polluant emissions

Polluant emissions

The estimation of pollutant emissions (NOx, HC, CO and particles) from tourism and light commercial vehicles cars follows a similar principle to that of estimating energy expenditure. Our algorithm estimates engine output emissions and considers the type of after-treatment system to estimate exhaust emissions.

Eco-driving indicators

We have developed a service which measures energy efficiency while driving. It helps drivers to reduce their fuel consumption, without necessarily increasing the duration of their journeys in order to resolve the complex issue of achieving 'minimum energy expenditure'.

The eco-driving (or driving efficiency) score measures the difference between the energy consumed and the minimum consumption possible for a journey. This score is caluclated by comparing the movement speed of the vehicle carried out by the driver with a reference speed for the route.

The reference velocity trajectory is obtained from the principle of least action, which is a foundation in mathematics and physics for motion analysis. By optimization, we calculate the minimum energy velocity profile that allows the same distance to be covered without extending the travel time.

Safety evaluation

Our safety analysis services deliver scores reflecting driver behaviour. They are established by studying the speed, acceleration and the energy expended where the tyre meets the road.

Driving safety is therefore evaluated using a dynamic model and our algorithm relies on the main physical characteristics of the vehicle (weight, wheelbase, engine, body, etc.) to estimate the tyre's adherence to the road throughout the journey.

In order to improve modelling of the energy expended between the wheel and the road, we are also able to account for data such as road type and weather conditions via third-party providers.

N.B. The safety score is measured independently of the speed limit. It only states the influence of the driving style upon the dynamic behaviour of the vehicle on the road. In addition, we are also developing a score for compliance with speed limits, which takes advantage of third-party APIs from the main mapping data suppliers.

Contextualisation of the driving analysis

For each journey we deliver overall scores as well as contextualised scores depending on the driving environment. This contextualisation is essential for evaluating driving performances and comparing drivers who are driving in the same conditions.

Our driving environment analysis engines are designed to categorise the journey starting with a measurement of travel speed. We can detect several environments:

- traffic jam,
- dense or fluid urban areas,
- areas outside of cities and high-speed roads.

In addition to this contextualisation representing traffic flow, we can also provide indications of the characteristics of roads travelled, obtained from mapping data.

Vehicle wear

Our predictive maintenance service has been designed to monitor the level of wear on the brake pads and tires in order to facilitate vehicle maintenance. The estimation of wear depends upon the amount of power dissipated at the point of contact between the tyre and the road or the brake pads and brake disc.

In order to estimate this variable, we model the vehicle dynamics while estimating the amount of energy expended during braking and at the point of contact between the tyre and the road:

- our service adapts to all types of transmission: front-wheel, rear-wheel or four-wheel drive
- it accounts for the characteristics of the tyres or brakes.

We have shown that traditional approaches to maintenance reminders based upon distance travelled are not enough to estimate the dates to change the tiyes or brakes. It is necessary to continuously monitor the vehicle and account for driving behaviour and the types of roads travelled.

Would you like to know more about
our data treatment platform?