… trajectory planning plays significant role in motion planning. This research addresses on the
trajectory planning … vehicle to travel, while planning global path on road network and traffic …

… the need of humanlike trajectory planning. Therefore, we develop a humanlike trajectory
planner using a general regression neural network (GRNN) by learning from the human-driven …

… In this paper, motion planning with LSTM trajectory prediction was utilized to avoid … LSTM
network to plan the human-like speed. The longitudinal and lateral human-like algorithms are …

… Table 1: Model complexity and the performance of trajectory planning: We highlight the …
We compute the average trajectory planning time per frame for each benchmark on a multi-…

… presents a trajectory planning algorithm for a robot operating in dynamic human environments.
… We formulate the problem as planning a minimal cost trajectory through a potential field, …

… , especially in a mixed traffic environment, where IVs and human-driven vehicles coexist [21…
In curve driving, humanlike trajectory planning is more valuable than simple planning that …

… proposes a personalized human-like lanechanging trajectory model that includes the
longitudinal driving behavior model and the lateral lane-changing trajectory planning model. The …

… human-like trajectory planning model using LSTM NN. This research proposes a trajectory
planning method by learning from experienced drivers aiming at human-like autonomous …

… human-like trajectories for use in autonomous vehicles as a possible solution to this issue.
We present a trajectory planning … driving scenarios to generate human-like trajectories. Speed …

… In this paper, the driver model is adopted to deal with the problem of trajectory planning,
then κctrl denotes curvature of the path to be planned. Vx and Vy are longitudinal and lateral …