In this paper, we study how to test the intelligence of an autonomous vehicle.
Comprehensive testing is crucial to both vehicle manufactories and customers. Existing …

平行学习— 机器学习的一个新型理论框架 Page 1 第43 卷第1 期 自动化学报 Vol. 43, No. 1 2017
年1 月 ACTA AUTOMATICA SINICA January, 2017 平行学习— 机器学习的一个新型理论框架 李 …

Effective simulation and testing environment is a vital part in the research of self-driving
vehicles. It is capable of testing self-driving software and hardware quickly in a variety of …

For unmanned ground vehicle (UGV) off-line testing and performance evaluation, massive
amount of traffic scenario data is often required. The annotations in current off-line traffic …

Achieving excellent generalization on perceiving real traffic scenarios with diversity is the
long-term goal for building robust autonomous driving systems. In this paper, we propose to …

Cognitive ability evaluation in intelligent vehicles is conventionally evaluated by classical
autonomous driving dataset, which lacks comprehensive annotations of driving difficulty …

In this paper, we present a novel framework to allow users to tour simulated traffic scenes
from the first-person view. Constructing 3-D scenes from road image sequences is in …

With increasing hardware computing power and model capacity, visual tasks for scene
cognitive understanding have attracted more attention, such as visual relationships …

Driving behavior is the main basis for evaluating the performance of an unmanned vehicle.
In simulation tests of unmanned vehicles, in order for simulation results to be approximated …

In this paper, we propose a framework for 3D traffic scenes construction based on semantic
segmentation using convolutional neural networks (CNNs). Firstly, the segmentation …