Autonomous vehicles must be able to react in a timely manner to typical and unpredictable
situations in urban scenarios. In this connection, motion planning algorithms play a key role …

Decision-making and motion planning are two core functionalities of intelligent vehicles. A
novel integrated decision-making and planning framework is presented for real-time and …

Developments in the Intelligent Transportation Systems (ITS) field show promising results at
increasing passengers comfort and safety, while decreasing energy consumption, emissions …

This paper presents an efficient hierarchical motion planning framework with a long
planning horizon for autonomous driving in structured environments. A 3D motion planning …

In last decades, great technology advances have been done related to the automotive
sector, especially in Advanced Driver Assistance Systems (ADAS) developed to improve …

This paper presents a framework for fast and robust motion planning designed to facilitate
automated driving. The framework allows for real-time computation even for horizons of …

Currently autonomous or self-driving vehicles are at the heart of academia and industry
research because of its multi-faceted advantages that includes improved safety, reduced …

Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …

A safe trajectory planning for on-road autonomous driving is a challenging problem owing to
the variety and complexity of driving environments. The problem should involve the …

Safe and adaptable motion planning for autonomous vehicles remains an open problem in
urban environments, where the variability of situations and behaviors may become …