As autonomous vehicles begin venturing on the urban road, rational decision making is
essential for driving safety and efficiency. This paper presents a situation-aware decision …

When applying autonomous driving technology to real-world scenarios, environmental
uncertainties make the development of decision-making algorithms difficult. Modeling the …

The Stadtpilot project aims at fully automated driving on Braunschweig's inner city ring road.
The TU Braunschweig's research vehicle “Leonie” is one of the first vehicles having the …

Autonomous vehicles need to perform social accepted behaviors in complex urban
scenarios including human‐driven vehicles with uncertain intentions. This leads to many …

Autonomous driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …

Real-world autonomous driving in city traffic must cope with dynamic environments including
other agents with uncertain intentions. This poses a challenging decision-making problem …

Urban intersections represent a complex environment for autonomous vehicles with many
sources of uncertainty. The vehicle must plan in a stochastic environment with potentially …

Driving autonomous vehicles safely through a complex urban environment remains a
difficult task. The sensor limitations, as well as the various occlusions in the urban …

In this paper, a point-based Markov Decision Process (QMDP) algorithm is used for robust
single-lane autonomous driving behavior control under uncertainties. Autonomous vehicle …

This work examines the hypothesis that partially observable Markov decision process
(POMDP) planning with human driver internal states can significantly improve both safety …