Spline-Based Motion Planning for Automated Driving

Search-based optimal motion planning for automated driving

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 several hundred meters and thus enabling automated driving in urban conditions. This is achieved through several features. Firstly, a convenient geometrical representation of both the search space and driving constraint...

Safe Motion Planning for Autonomous Driving

Self-driving cars have the potential to revolutionize transportation by making it cheaper, safer, and more efficient. In this thesis we describe a novel motion planning system, which translates high-level navigation goals into low-level actions for controlling a vehicle. Specifically, the motion planning system is responsible for choosing at each time step an appropriate velocity and steering a...

Real-Time Motion Planning 
 and
 Autonomous Driving

Smooth trajectory planning for fully automated passengers vehicles - spline and clothoid based methods and its simulation

A new approach for mobility, providing an alternative to the private passenger car, by offering the same flexibility but with much less nuisances, is emerging, based on fully automated electric vehicles. A fleet of such vehicles might be an important element in a novel individual, door-to-door, transportation system to the city of tomorrow. For fully automated operation, trajectory planning met...

Planning Graph Based Heuristics for Automated Planning

One of the most successful algorithms in the last few years for solving classical planning problems is Graphplan [3]. This algorithm can be seen as a disjunctive version of forward state space planners. The algorithm has two interleaved phases: a forward phase where a polynomial-time data structure called ”planning graph” is incrementally extended, and a backward phase where that planning graph...