… 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 …

… example of a path planner for autonomous vehicles. Many … The latter case represents that
the observed MDP behavior … there is a non-zero probability to violate the specification after the …

… in the MDP behavior, we consider complementing the matrix T with transition probabilities, …
M Q ) has a probability associated with how likely each type of car is to pass the test. …

… [21] applied probabilistic MDP-Behavior planning for cars. … of surrounding vehicles, the
ego vehicle-surrounding vehicle … information of the surrounding vehicles entry or exit from an …

… , [5] uses probabilistic reachable sets to predict the safety of the ego vehicle, [6] treats the
problem with stochastic drift counteraction optimal control, and [7, 8] employ MDPs to plan the …

… In addition, the probabilistic methods are always used to make decision for autonomous
vehicles in complex uncertain environments. For example, Markov decision processes (MDPs) …

… the larger longitudinal space and minimum driving effort along with higher transition
probability due to the lower threat of the vehicles maximizes the sum of expected payoff in the left …

… with human-driving vehicles. To harmoniously share traffic resources, self-driving vehicles
need to … Taking on-road driving for example, self-driving vehicles are supposed to behave in a …

… the privacy of the transition probabilities in a Markov decision … probabilities using a mechanism
that provides differential privacy. Then, based on the privatized transition probabilities, we …