Autonomous vehicles need to plan at the task level to compute a sequence of symbolic
actions, such as merging left and turning right, to fulfill people's service requests, where …

Aiming at the problem of low confidence and low success rate of vehicle navigation system,
a dynamic navigation system based on binocular vision is proposed and designed. The …

Different from urban environment with high-precision map, off-road environment lacks rich
priori road structure information and precise location information, which is a huge challenge …

Abstract The Intelligent Driver Model was introduced in 2000 by M. Treiber et al. as a
mathematical car following model for traffic microsimulation. It is an obvious question …

This paper presents three different approaches to inject a location information in semantic
segmentation Convolutional Neural Networks (CNN) applied to urban scenes. The …

We present a novel approach to automatically identify driver behaviors from vehicle
trajectories and use them for safe navigation of autonomous vehicles. We propose a novel …

As an alternative to explicit programming for robots, Deep Imitation learning has two
drawbacks: sample complexity and covariate shift. One approach to Imitation Learning is …

Self-driving simulators play a key role in the development and deployment of unmanned
vehicle algorithms. While the ad-hoc usage of simulation in self-driving and robotics …

Among the available communication systems, vehicular networks are emerging as one of
the most promising and yet most challenging instantiations of mobile ad hoc network …

The paper describes the design, implementation and user evaluation of utility-based and
goal-based intelligent learning agents for smart shopping cart. In keeping user's shopping …