This paper presents a longitudinal and lateral motion planning method for driver assistance
systems in urban scenarios. We proposed a Bayesian network based motion planner to …

In unsignalized intersections with poor visibility, proactive driving with hazard anticipation is
required in order to avoid collisions with other traffic participants from a blind corner …

The predictive motion prediction of surrounding vehicles is an essential precondition for
precise collision risk assessment and path planning. In this paper, we propose a motion …

This paper presents a probabilistic framework for decision-making in collision avoidance
systems, targeting all types of collision scenarios with all types of single road users and …

This work proposes an active collision avoidance between autonomous driving vehicle and
pedestrian with motion uncertainty under urban road. A candidate trajectory planning …

This paper presents an approach for predictive driving when facing blind intersections
based on expert data. Expert drivers anticipate and avoid potential dangerous situations. In …

This study proposes a motion planning and control system based on collision risk potential
prediction characteristics of experienced drivers. Recently, automatic braking systems have …

Risk predictive driving is essential to maintain safety while passing a parked vehicle, which
is one of typical high risk traffic situations because a pedestrian might suddenly dart out from …

In the present studies of autonomous driving systems, motion planning of automated
vehicles in complex traffic scenarios is a tough issue. The problem of adjusting automated …

Humanlike driving is significant in improving the safety and comfort of automated vehicles.
This paper proposes a personalized motion planning method with driver characteristics in …