Braking distance algorithm for autonomous cars using road surface recognition

TLDR: This research work describes and experiments the method for recognizing road surface profile and calculating braking distance, which when installed on normal cars can also be used to create a database of road surfaces, especially in cities, which can be shared with other cars.

Abstract: India is yet to accept semi/fully – autonomous cars and one of the reasons, was loss of control on bad roads. For a better handling on these roads we require advanced braking and that can be done by adapting electronics into the conventional type of braking. In Recent years, the automation in braking system led us to various benefits like traction control system, anti-lock braking system etc. This research work describes and experiments the method for recognizing road surface profile and calculating braking distance. An ultra-sonic surface recognition sensor, mounted underneath the car will send a high frequency wave on to the road surface, which is received by a receiver with in the sensor, it calculates the time taken for the wave to rebound and thus calculates the distance from the point where sensor is mounted. A displacement graph will be plotted based on the output of the sensor. A relationship can be derived between the displacement plot and roughness index through which the friction coefficient can be derived in Matlab for continuous calculation throughout the distance travelled. Since it is a non-contact type of profiling, it is non-destructive. The friction coefficient values received in real-time is used to calculate optimum braking distance. This system, when installed on normal cars can also be used to create a database of road surfaces, especially in cities, which can be shared with other cars. This will help in navigation as well as making the cars more efficient.