NAVARCHOS features a novel and robust ECO driving assessment mechanism driven by AI. A complex algorithm is automatically estimating the performance of each driver taking into account a number eco driving related parameters, collected from each driver’s vehicle, through the following process:
- Raw GPS trajectories are projected into GIS data (road network)
- GIS Trajectories are clustered to group similar routes
- Fuel consumption data is analyzed over similar and frequent routes
- Factors that mostly affecting the increase in fuel consumption such as high/low speed, high RPM and driving violations (hard braking, hard acceleration, idling, hard cornering, etc.) are identified
- Driver rating is presented to driver dashboard
- Driver ranking is presented to fleet manager dashboard
- Comparative figures on actual vs optimal fuel consumption, distance covered, and travel time are presented to both driver and fleet manager. Optimal values are evaluated over best (shortest) routes.
Beyond the ECO driving assessment algorithm, NAVARCHOS provides more than 50 charts illustrating the status and trends of parameters related to the ECO profile and behavior.
More specifically, NAVARCHOS provides comparisons on fuel consumption, distance covered, travel time and fuel efficiency against all drivers of a specific group of an organization, in a way that less obvious and more concrete conclusions can be extracted for the ECO driving behavior of each driver.