No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Decision-making and planning are the core aspects of autonomous driving systems. These
factors are crucial for improving the safety, driving experience, and travel efficiency of …

With heterogeneous traffic agents moving at unprotected phase, severe crossing conflicts
are witnessed at mixed-flow intersections, especially when left-turning vehicles are …

An essential and challenging task for autonomous vehicles (AVs) is turning at mixed-flow
intersections when they interact with motorized, non-motorized and pedestrian traffic …

For a decade, researchers have focused on the development and deployment of road
automated mobility. In the development of autonomous driving embedded systems, several …

Turning behaviour is one of the most challenging driving manoeuvres that take place at
intersections. Autonomous vehicles (AVs) are often overly conservative in these scenarios …

Information on the trajectories of turning vehicles at signalized intersections can be used in
numerous applications, such as movement planning of autonomous vehicles, realistic …

Performing a left turn in a non-protected phase at mixed-flow intersections is one of the most
challenging driving maneuvers. In general, there are three typical behavioral features during …

With the integration of Autonomous Vehicles (AVs) into our transportation systems, their
harmonious coexistence with Human-driven Vehicles (HVs) in mixed traffic settings …

This paper aims at developing a convolutional neural network (CNN)-based tool that can
automatically detect the left-turning vehicles (right-hand traffic rule) at signalized …