Motion (physics)

Quantum mechanics

Algorithm

Control (management)

Discretization

Computer security

Telecommunications

Computer science

Collision

Mathematical optimization

Collision avoidance

Physics

Trajectory

Simulation

Mathematics

Astronomy

Flow (mathematics)

Terminal (telecommunication)

Mathematical analysis

Artificial intelligence

Geometry

Term (time)

Control theory (sociology)

State (computer science)

Key (lock)

The International Journal of Robotics Research

This paper deals with the trajectory generation problem faced by an autonomous vehicle in moving traffic. Being given the predicted motion of the traffic flow, the proposed semi-reactive planning strategy realizes all required long-term maneuver tasks (lane-changing, merging, distance-keeping, velocity-keeping, precise stopping, etc.) while providing short-term collision avoidance. The key to comfortable, human-like as well as physically feasible trajectories is the combined optimization of the lateral and longitudinal movements in street-relative coordinates with carefully chosen cost functionals and terminal state sets (manifolds). The performance of the approach is demonstrated in simulated traffic scenarios.

Optimal trajectories for time-critical street scenarios using discretized terminal manifolds