… local motion planning framework for autonomous vehicles based on resistance network and
model predictive control,” … -physical systems, hybrid systems, advanced vehicle control, and …

… in driving scenarios … -based motion planning algorithm for automated vehicle participating
at the DARPA Urban Challenge (DUC) is presented in [24] and [25]. A hybrid method based on …

… MOTION planning for autonomous vehicle functions is a vast and long-researched area
using a wide variety of … This work uses mixed grid and ego state observation, hence utilizing …

This article presents a model-based motion planning and control system for autonomous
vehicles and its experimental validation. The system consists of four modules: 1) global routing; …

… planning methods for autonomous driving. Broadly speaking, planning methods for autonomous
driving can … in a mixedtraffic highway scenario. Beyond simple tasks, MARL approaches …

… is a mixed environment of normal vehicles and autonomous … -making, motion planning, and
control framework for overtaking … , driving mode decision, motion planning, and control. Each …

… The graph-based search methods such as A*, state lattice, hybrid A*, … path planning (upper)
generates the macro trajectory based on the discrete information of objects and traffic control …

… planning and tracking for autonomous vehicle based on state lattice and model predictive
control… Guided hybrid A-star path planning algorithm for valet parking applications. In: 2019 5th …

… region and vehicle shape. Zhang et al. [16] integrate trajectory planner and tracking controller
for autonomous vehicles to … platoon using hybrid automata,’’ IEEE Trans. Intell. Transp. …

… mobility, a personalized approach of trajectory planning and control based on user
preferences is developed for lane-change of autonomous vehicles in this paper. First, a safe area …