Intelligent connected vehicles (ICVs) are believed to change people's life in the near future
by making the transportation safer, cleaner and more comfortable. Although many …

This paper describes lane change motion planning with a combination of probabilistic and
deterministic prediction for automated driving under complex driving circumstances. The …

As pedestrians are one of the most vulnerable traffic participants, their motion prediction is of
utmost importance for intelligent transportation systems. Predicting motions of pedestrians is …

Trajectory planning has generally been framed as finding the lowest cost one from a set of
trajectory candidates, where the cost function has been hand-crafted with carefully tuned …

This paper proposes the decision-making framework of lane change behavior based on
Hierarchical State Machine (HSM) and we build distributed control system architecture …

Motion planning in on-road urban driving is usually stated as an optimization problem in a
multi-dimensional space that presents a high complexity in obtaining a global optimal …

Human-like driving is of great significance for safety and comfort of autonomous vehicles,
but existing trajectory planning methods for on-road vehicles rarely take the similarity with …

It is crucial for automated vehicles to interact with the surrounding vehicles properly in urban
environment that can make both passengers and surrounding drivers feel safe and at ease …

Autonomous driving is the research frontier of vehicle engineering and lay a significant
impact on automobile industry. Through analysis on Co-word network and technology …

Human drivers navigate the roadways by balancing values such as safety, legality, and
mobility. An autonomous vehicle driving on the same roadways as humans likely needs to …