… In Scenario #2, the traffic signal’s timing plan was not changed but the autonomous cars
were made to travel slowly in order to avoid being caught in the ‘dilemma zone’ at the end of …

… an autonomous car to perform cooperative social behavior. Accelerations of cars merging
… [8] generate cooperative planning for autonomous highway driving using Monte-Carlo Tree …

We propose a learning-based method for the longitudinal control of an autonomous vehicle
on the highway. We use a driver model to generate acceleration inputs which are used as a …

… planning problem for autonomous vehicles driving in realistic urban environments. To solve
the complex navigation problem, we adopt a hierarchical motion planning … planning task is …

… There are various methods in the literature to address the problem of on-road motion
planning for autonomous cars. Readers are referred to Bautista et al. [1] for a review on these …

… Trajectory planning is a significant component of autonomous … of autonomous vehicle.
Different prediction horizons and coordinate transformation are adopted to optimize the planning. …

… concepts of autonomous cars, as well as their components. Section 3 is a survey of RAs
for autonomous cars. Section 4 … Planning – this functionality determines the behavior of the …

… and safety of the car. As long as we can assign a driver to an autonomous car, even though
… has to take responsibility for the moral decisions regarding car operation. In this vein, a self-…

… TACTICAL DECISION MAKING FRAMEWORK This paper introduces a framework that
combines planning and learning for tactical decision making in the autonomous driving domain. …

… in a likely hallmark of autonomous vehicles—their safety. Given a risky situation, the
autonomous car slows down and yields. Even at midblock and unmarked crosswalks, 2 the cars—…