Claims:WE CLAIM:
1. A method for determining safe navigation of autonomous vehicle, the method comprising:
determining, by an Electronic Control Unit (ECU) (103) of an autonomous vehicle, current location of the autonomous vehicle, at an instant of time, based on orientation and location information of the autonomous vehicle;
determining, by the Electronic Control Unit (ECU) (103), one or more pre-defined vehicle parameters and surrounding infrastructure data;
determining, by the Electronic Control Unit (ECU) (103), traffic density at current route of the autonomous vehicle for a predefined time and distance from the current location of the autonomous vehicle, based on the surrounding infrastructure data for the current route and the current location of the autonomous vehicle;
predicting, by the Electronic Control Unit (ECU) (103), traffic density at one or more alternate routes for a predefined time and distance from the current location of the autonomous vehicle, based on the surrounding infrastructure data for the one or more alternate routes; and
selecting, by the Electronic Control Unit (ECU) (103), a route for navigating the autonomous vehicle based on the one or more pre-defined vehicle parameters of the autonomous vehicle, the traffic density at the current route and the traffic density at the one or more alternate routes for safely navigating the autonomous vehicle.

2. The method as claimed in claim 1, wherein the orientation information is determined based on data from Inertial Measurement Unit sensor.

3. The method as claimed in claim 1, wherein the one or more predefined vehicle parameters comprises translational speed, turning speed, engine power, vehicle speed limit, vehicle turning capability, vehicle acceleration limit, vehicle deceleration limit, vehicle tyre pressure and vehicle weight.

4. The method as claimed in claim 1, wherein the surrounding infrastructure data comprises maximum deceleration of trailing and front vehicle, maximum acceleration of trailing and front vehicle, maximum speed difference between vehicles in front and rear, minimum headway distance between front and rear vehicle, time before lane change, collision time gain between front and rear vehicles and minimum lateral distance for overtaking vehicles.

5. The method as claimed in claim 1 further comprising prioritizing the one or more alternate routes based on the traffic density.

6. The method as claimed in claim 1, wherein the traffic density at the at one or more alternate routes is predicted based on a threshold time, threshold distance, a threshold Field of View (FOV), location, orientation and speed details of vehicles in the one or more alternate routes, distance between the autonomous vehicle and vehicles in the one or more alternate routes and distance and an area of the one or more alternate routes.

7. The method as claimed in claim 1 further comprising providing continuous feedback by assessing a plurality of configuration parameters and the determined alternate route for the autonomous vehicle.

8. The method as claimed in claim 1 further comprising determining speed control for the autonomous vehicle based on the traffic density at the current route.

9. The method as claimed in claim 1 further comprising determining Expected Time Arrival (ETA) for the autonomous vehicle based on the one or more predefined vehicle parameters and a calculated distance of the route.

10. The method as claimed in claim 1 further comprising monitoring the traffic density at the selected route for a predefined time and distance.

11. The method as claimed in claim 10 further comprising determining an alternate route for the autonomous vehicle from one or more alternate routes based on the monitoring.

12. An Electronic Control Unit (ECU) (103) of an autonomous vehicle for determining safe navigational path based on traffic condition, comprising:
a processor (111); and
a memory (109) communicatively coupled to the processor (111), wherein the memory (109) stores processor instructions, which, on execution, causes the processor (111) to:
determine current location of the vehicle, at an instant of time, based on orientation and location information of the vehicle;
determine one or more pre-defined vehicle parameters and surrounding infrastructure data;
determine traffic density at current route of the autonomous vehicle for a predefined time and distance from the current location of the autonomous vehicle, based on the surrounding infrastructure data for the current route and the current location of the autonomous vehicle;
predict traffic density at one or more alternate routes for a predefined time and distance from the current location of the autonomous vehicle, based on surrounding infrastructure data for the one or more alternate routes; and
select a route for navigating the autonomous vehicle based on the one or more pre-defined vehicle parameters, the traffic density at the current route and the traffic density at the one or more alternate routes for safely navigating the autonomous vehicle.

13. The ECU (103) as claimed in claim 12, wherein the processor determines the orientation information based on data from Inertial Measurement Unit sensor.

14. The ECU (103) as claimed in claim 12, wherein the one or more predefined vehicle parameters comprises translational speed, turning speed, engine power, vehicle speed limit, vehicle turning capability, vehicle acceleration limit, vehicle deceleration limit, vehicle tyre pressure and vehicle weight.

15. The ECU (103) as claimed in claim 12, wherein the surrounding infrastructure data comprises maximum deceleration of trailing and front vehicle, maximum acceleration of trailing and front vehicle, maximum speed difference between vehicles in front and rear, minimum headway distance between front and rear vehicle, time before lane change, collision time gain between front and rear vehicles and minimum lateral distance for overtaking vehicles.

16. The ECU (103) as claimed in claim 12, wherein the processor prioritises the one or more alternate routes based on the traffic density.

17. The ECU (103) as claimed in claim 12, wherein the traffic density at the at one or more alternate routes is predicted based on threshold time, threshold distance, a threshold Field of View (FOV), location, orientation and speed details of vehicles in the one or more alternate routes, distance between the autonomous vehicle and vehicles in the one or more alternate routes and distance and an area of the one or more alternate routes.

18. The ECU (103) as claimed in claim 12, wherein the processor provides continuous feedback by assessing a plurality of configuration parameters and the determined alternate route for the autonomous vehicle.

19. The ECU (103) as claimed in claim 12, wherein the processor determines speed control for the autonomous vehicle based on the traffic density at the current route.

20. The ECU (103) as claimed in claim 12, wherein the processor determines Expected Time Arrival (ETA) for the autonomous vehicle based on the one or more pre-defined vehicle parameters and a calculated distance of the route.

21. The ECU (103) as claimed in claim 12, wherein the processor monitors the traffic density at the selected route for a predefined time and distance.

22. The ECU (103) as claimed in claim 21, wherein the processor determines an alternate route for the autonomous vehicle from one or more alternate routes based on the monitoring.

Dated this 5th day of November, 2018

R Ramya Rao
Of K&S Partners
Agent for the Applicant
IN/PA-1607 , Description:TECHNICAL FIELD
The present subject matter is related in general to autonomous vehicle, more particularly, but not exclusively to a method and system for determining safe navigation of autonomous vehicle.