Safe Autonomous Driving

In the past decade, autonomous systems have attracted the attention of many researchers and companies on a global scale. To fully deploy highly automated driving technologies in more general settings, such as urban driving, the autonomous system needs to sense the surrounding environment reliably and interact with it safely. To that end, the open problems related to safe autonomous driving span from designing cost-effective, robust, and reliable sensors to developing powerful perception and motion planning and control algorithms. 

Exploring Cybersecurity for Electric Vehicles

With the development of networking technology for the Internet of Vehicles (IoV), there are opportunities for persistent and dangerous cyber-attacks. If these threats are not detected (especially for safety-critical applications), they can lead to catastrophic failure and substantial economic loss.

On the Road to a Smarter Future

Improving Autonomous Driving with Event-Based Neuromorphic Vision

How Advanced 5G and Beyond Networks Can Unlock the IoT Revolution

How Advanced 5G and Beyond Networks Can Unlock the IoT Revolution

Deep Learning Helps Autonomous Vehicles Operate in Extreme Weather

Similar to human drivers, adverse weather conditions still pose as a major obstacle for autonomous vehicles (AVs). Using a deep learning framework, researchers have developed a new detection and tracking system aimed at solving how AVs “see” their surroundings.

New System Could Bring Autonomous Technology to More Vehicles

Autonomous vehicles have gone from hype to reality in recent years, and companies of all sizes are now looking to hop on the driverless bandwagon.