A new data-driven technique for obstacle avoidance in autonomous vehicles is reported in the International Journal of Vehicle ...

Self-driving cars will soon be able to "think" like human drivers under complex traffic environments, thanks to a cognitive encoding framework built by a multidisciplinary research team from the ...

The automotive industry is primed for rapid innovation because of its background of widely available data on roads, vehicles, and the environment in general. Two key areas stand out: freight ...

However, the technology for functionally safe GNSS/INS localization in autonomous vehicles is still not fully established. This gap is particularly crucial in safety-critical applications, where ...

According to Nvidia CEO Jensen Huang, AlexNet, an AI model from over a decade ago, is what sparked the company's investment in autonomous vehicles.

3D mapping and localization are essential tasks for autonomous vehicles, as they allow them to perceive their surroundings and navigate safely and efficiently. However, choosing the best sensors ...

Intelligent vehicles and their autonomous driving are the current development direction of the automotive industry, but the current autonomous driving algorithms have significant errors in lateral ...

Precise and real-time localization is the key for autonomous vehicles (AVs) to solve traffic, environmental problems and support intelligent vehicle applications. Existing AV localization methods ...

3D mapping and localization are essential tasks for autonomous vehicles, as they allow them to perceive their surroundings and navigate safely and efficiently. However, choosing the best sensors ...