… autonomous vehicles will … self-driving autonomous vehicles that can perform all necessary
operations on their own. Hence, there is no need for infrastructure development or the use of …

… learns a lane-changing behavior by taking all other vehicles as part of the driving … applied
to autonomous driving [13–16], with the objective of accomplishing autonomous driving tasks …

… the risks in self-driving vehicles. Risk … self-driving vehicles by proposing new hybrid MCDM
methods based on the Analytic Hierarchy Process (AHP), the Technique for order preference …

… human-driven vehicles. To this end, the behaviors and characteristics of human drivers
should be considered in the automated driving design. If AVs’ driving behaviors are considered …

… To show how MARL could be specifically relevant to autonomous driving, we have in
Table 1 mapped the double merge scenario to MARL approaches at various M levels. …

… An illustration of sensors configuration in an autonomous vehicle, towards driving under
adverse weather conditions. Sensor coverage denotes the general operating directions instead …

… This paper proposes a stochastic model for mixed traffic flow with human-driven vehicles (HVs)
and automated vehicles (AVs). The model is formulated in Lagrangian coordinates …

… This section summarizes NR key features that will fulfill the diverse and stringent requirements
of autonomous driving from the network, user, application, and use case perspectives. …

… autonomous vehicles, which along with perceived usefulness determine the behavioral
intention (to use autonomous vehicles). … usefulness, perceived ease of use, but also two types of …

… We use a single time-step input since prior works on IL for autonomous driving have shown
… We use the L1 distance between the predicted trajectory, π(X), and the expert trajectory, W, …