Efficient reasoning about the spatial and temporal structure of the environment is crucial for
perception in autonomous driving, particularly in an end-to-end approach. Although different …

This research introduces an innovative approach for End-to-End steering angle prediction
and its control in electric power steering (EPS) systems. The methodology integrates transfer …

Real‐time prediction of vehicle trajectory at unsignalized intersections is important for real‐
time traffic conflict detection and early warning to improve traffic safety at unsignalized …

Deep learning techniques, particularly convolutional neural networks (CNNs), have
exhibited remarkable performance in solving visionrelated problems, especially in …

The development of autonomous vehicles has grown significantly recently due to the
promise of improving safety and productivity in cities and industries. The scene perception …

Autonomous cars are smart vehicles that are capable of sensing their surroundings and
navigating accordingly without or less human involvement. Such cars are vulnerable to …

Steering angle controller is a core module of autonomous vehicles, where a slight
miscalculation can cause severe accidents. Following safety precautions, development of …

Existing end-to-end networks for steering angle prediction usually use images generated by
standard cameras as input. However, standard cameras are susceptible to poor lighting …

Imitation learning is employed to learn sensorimotor coordination for steering angle
prediction in an end-to-end fashion requires expert demonstrations. These expert …

Autonomous racing has rapidly gained research attention. Traditionally, racing cars rely on
2D LiDAR as their primary visual system. In this work, we explore the integration of an event …