Abstract: This disclosure relates to method and system for validating an Autonomous Vehicle (AV) stack. The method may include receiving an Operational Design Domain (ODD) and real-world data for evaluating at least one of an Advanced Driver Assistance System (ADAS) and the AV. The ODD is based on at least one feature of at least one of the ADAS and the AV. For each of a plurality of iterations, the method may further include generating a driving scenario based on the ODD of the AV and the real-world data through a Quality of Ride Experience (QoRE)-aware cognitive engine, plugging and running at least one of the ADAS and the AV algorithm based on the driving scenario, and determining a set of performance metrics corresponding to the at least one feature of at least one of the ADAS and the AV in the driving scenario based on the simulating.

Abstract: Disclosed subject matter relates to a field of vehicle navigation system that performs a method for navigating an autonomous vehicle at an intersection of roads. An intersection management system may receive sensor data including at least one of depth of an object, images and a video of environment surrounding the autonomous vehicle. Further, traffic police and auxiliary objects associated with each traffic police are detected from plurality of objects of interest present in the images, when the autonomous vehicle is within a predefined distance from an intersection of roads. Thereafter, a correlation matrix comprising inferred data related to each traffic police and the auxiliary objects may be generated. Based on the correlation matrix, the video and the images, a gesture of the traffic police may be determined accurately. Finally, navigation information may be determined based on the correlation matrix and determined gesture, for navigating the autonomous vehicle.

Abstract: This disclosure relates to method and system for validating an Autonomous Vehicle (AV) stack. The method may include receiving an Operational Design Domain (ODD) and real-world data for evaluating at least one of an Advanced Driver Assistance System (ADAS) and the AV. The ODD is based on at least one feature of at least one of the ADAS and the AV. For each of a plurality of iterations, the method may further include generating a driving scenario based on the ODD of the AV and the real-world data through a Quality of Ride Experience (QoRE)-aware cognitive engine, plugging and running at least one of the ADAS and the AV algorithm based on the driving scenario, and determining a set of performance metrics corresponding to the at least one feature of at least one of the ADAS and the AV in the driving scenario based on the simulating.

Abstract: The present disclosure relates to a method of generating a surround view of a vehicle platoon and a device thereof. A surround view generating device for a vehicle in the vehicle platoon acquires a local surround view of the vehicle and at least one of a truncated local surround view associated with one or more preceding vehicles and a truncated local surround view associated with one or more following vehicles in the vehicle platoon. Further, the surround view generation device generates a surround view of the vehicle platoon using the local surround view of the vehicle, the truncated local surround view associated with the one or more preceding vehicles, and the truncated local surround view associated with the one or more following vehicles. Finally, the surround view generating device navigates the vehicle in the vehicle platoon based on the surround view of the vehicle platoon.

Abstract: Disclosed subject matter relates to a field of vehicle navigation system that performs a method for navigating an autonomous vehicle at an intersection of roads. An intersection management system may receive sensor data including at least one of depth of an object, images and a video of environment surrounding the autonomous vehicle. Further, traffic police and auxiliary objects associated with each traffic police are detected from plurality of objects of interest present in the images, when the autonomous vehicle is within a predefined distance from an intersection of roads. Thereafter, a correlation matrix comprising inferred data related to each traffic police and the auxiliary objects may be generated. Based on the correlation matrix, the video and the images, a gesture of the traffic police may be determined accurately. Finally, navigation information may be determined based on the correlation matrix and determined gesture, for navigating the autonomous vehicle.

Abstract: The present disclosure relates to a method of generating a surround view of a vehicle platoon and a device thereof. A surround view generating device for a vehicle in the vehicle platoon acquires a local surround view of the vehicle and at least one of a truncated local surround view associated with one or more preceding vehicles and a truncated local surround view associated with one or more following vehicles in the vehicle platoon. Further, the surround view generation device generates a surround view of the vehicle platoon using the local surround view of the vehicle, the truncated local surround view associated with the one or more preceding vehicles, and the truncated local surround view associated with the one or more following vehicles. Finally, the surround view generating device navigates the vehicle in the vehicle platoon based on the surround view of the vehicle platoon.