… For the discrete or categorical random variables we use all the non-zero probability … for
closeness to other vehicles and crash (as a function of the velocity of the involved vehicles); for …

… planning problem for autonomous vehicles in traffic. We build a stochastic Markov decision
process (MDP) model to represent the behaviors of the vehicles… to different vehicle velocities, …

… An MDP is a mathematical framework that probabilistically models the interaction between …
1 T is the state transition probability matrix that provides the probability of the system transition …

… Since we are assuming that the subject vehicle is always able to split from its current platoon,
the probability of completing this action is the probability of successfully changing lanes …

… The interactive scene prediction [17] method generates future trajectories by predicting the
future motion of all the mobile vehicles. Then they compute the collision probability of each of …

… , the risk value of each predicted maneuver for the target vehicle is multiplied by its
probability of the relevant maneuver based on the prediction results. As demonstrated in Fig.5(a), …

… Without a high penetration of vehicle-to-vehicle communication an autonomous vehicle has
… combinatorial motion planning algorithm without the need for inter vehicle communication …

… This section describes how we infer the probability of the policies executed by other cars
and their parameters. Our behavioral anticipation method segments the history (ie, time-series …

… We achieve this by adding transitions and updating transition probabilities from experience
… not require powerful hardware for online planning in the vehicle and delivers a solution with …

… We can determine the vehicles inside the AoA and categorize these vehicles based on the
… we can obtain the probability of action A1 for each scenario by multiplying the probabilities of …