… probabilistic assessment of road lanes and a deterministic assessment of the inter-vehicular
gaps. For the probabilistic … Probabilistic MDP-Behavior Planning for Cars. In 2011 IEEE 14th …

… We refer to our autonomous vehicle of interest as the “ego-vehicle”. … Thus more recent work
has focused on probabilistic decision making under machine learning approaches [30, 69], …

… motion planning. Specifically, we assume a setting in which the transition probabilities can be
… to ensure that the planning task can be completed with sufficient probability of success. We …

This paper proposes the usage of a bio-inspired action selection mechanism, known as
multi-hypothesis sequen-tial probability ratio test (MSPRT), as a decision making tool in the field …

… vehicle i interacts with the adjacent vehicle j ∈ A(i), where A(i) contains indices of all the
adjacent vehicles around vehicle i. … zero probabilities in π for the unsafe trajectories γunsafe(si …

In safety-critical systems such as autonomous driving systems, behavior planning is a
significant challenge. The presence of numerous dynamic obstacles makes the driving …

… In this work, the road network is made up of straight lanes and all vehicles except the Ego
vehicle (controlled by the RL agent) follow a simple and realistic behavioral model that …

… Probabilistic MDP-Behavior Planning for Cars' further describes how to cope with uncertain
systems with expanding methods of MDP [2]. Other articles recommend a useful package, …

… and development of autonomous vehicles around the world using the … vehicle area. Therefore,
this paper presents the architecture design for the navigation of an autonomous vehicle in …

… Otto and Leon 26 predicted vehicle trajectory by building various situation models. Because
deterministic prediction methods have limits, probabilistic prediction methods have been …