Autonomous vehicle (AV) technology can provide a safe and convenient transportation
solution for the public, but the complex and various environments in the real world make it …

Noisy sensing, imperfect control, and environment changes are defining characteristics of
many real-world robot tasks. The partially observable Markov decision process (POMDP) …

In this manuscript, we introduce a real-time motion planning system based on the Baidu
Apollo (open source) autonomous driving platform. The developed system aims to address …

Automated driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …

Connected and automated vehicle (CAV) technologies have been developed to improve
traffic safety, mobility, and environmental impacts throughout the years. One of the enabling …

It is critical to predict the motion of surrounding vehicles for self-driving planning, especially
in a socially compliant and flexible way. However, future prediction is challenging due to the …

This paper reports on an integrated inference and decision-making approach for
autonomous driving that models vehicle behavior for both our vehicle and nearby vehicles …

In this article, we present an efficient planning system for automated vehicles in highly
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …

Anticipating possible behaviors of traffic participants is an essential capability of
autonomous vehicles. Many behavior detection and maneuver recognition methods only …

Autonomous vehicles need to perform social accepted behaviors in complex urban
scenarios including human‐driven vehicles with uncertain intentions. This leads to many …