Falko Saust

Stadtpilot: Driving autonomously on Braunschweig's inner ring road

The development of the autonomous vehicle named “Caroline” for the 2007 DARPA Urban Challenge was a great opportunity to demonstrate the abilities of the Technische Universität Braunschweig in the research field of autonomous driving. Among 11 teams out of the initially 89, the CarOLO team mastered the challenges to qualify for the final DARPA Urban Challenge event. Based on this experience, the Technische Universität Braunschweig is currently working on the follow-up project “Stadtpilot” with the objective to drive fully autonomously on Braunschweigs entire ring road, which is known as the arterial road of its inner city traffic. This paper introduces the “Stadtpilot”-Project in the context of the Urban Challenge experience and identifies the differences to previous activities in this research context. The scientific claim will be shown in contrast to the Urban Challenge scenario. Completely new concepts are required to master the challenges of realizing autonomous driving in the domain of Braunschweigs inner ring road. An approach for the comprehensive treatment of path-planned sections is shown that realizes complex and precise autonomous driving maneuvers in a real urban environment and is observed as the first major success of the “Stadtpilot”-Project. Curvature optimized trajectories are generated over the whole roadway that are independent from the way driving decisions are found.

Stadtpilot: First fully autonomous test drives in urban traffic

The Stadtpilot project aims at autonomous driving on Braunschweigs inner city ring road. For this purpose, an autonomous vehicle called “Leonie” has been developed. In October 2010, after two years of research, “Leonies” abilities were presented in a public demonstration. This vehicle is one of the first worldwide to show the ability of driving autonomously in real urban traffic scenarios. This paper describes the legal issues and the homologation process for driving autonomously in public traffic in Braunschweig, Germany. It also dwells on the Safety Concept, the system architecture and current research activities.

Exploitability of vehicle related sensor data in cooperative systems

This paper shows how extended vehicle related sensor data is gained and used within the cooperative system developed in the project KOLINE. This system aims at coordinating traffic in order to achieve a reduction of delay and emissions in urban networks by exchanging information between traffic signals and approaching vehicles. Besides receiving information about the signal program and traffic state at the intersection the vehicle also uses data of multiple sensors and different sensor technologies. This allows the creation of a redundant representation of the vehicles environment which is used to improve the vehicles approach to intersections. Additionally, the information can be used by the infrastructure to improve the performance of the adaptive traffic control system by using it for tailback approximation and for the calibration of the underlying traffic model.

Safe, dynamic and comfortable longitudinal control for an autonomous vehicle

Driver assistance systems are commonly available in many vehicles. There are systems for safety functions like the Electronic Stability Control, Automatic Traction Control, Anti-lock Brake System and automatic emergency braking. There are also systems for comfort functions like adaptive cruise control with stop and go functionality and combined safety and comfort functions like lane keeping and side-wind assistance. A control system consisting of all of these systems would allow comfortable automatic vehicle guidance on highways. In an urban environment, like in the Stadtpilot project, requirements on driver assistance systems are higher, especially in the case of full autonomous driving. An essential part of an autonomous vehicle control system is a longitudinal controller for acceleration and deceleration of the vehicle. This longitudinal control system has to take care of many more conditions than an assistance system. E.g. it needs to perceive and calculate road and weather conditions with its sensors, which usually is a task a human driver does instinctively. The present paper describes how the autonomous vehicle Leonie is able to adapt its longitudinal control to changing road and weather conditions by calculating a so called Grip Value and gives an outlook how this parameter affects whole vehicle guidance.

Comprehensive treated sections in a trajectory planner for realizing autonomous driving in Braunschweig'S urban traffic

With the announcement of the “Stadtpilot”- Project the Technische Universität Braunschweig has accepted the challenge of guiding a vehicle fully autonomously in the complex environment of Braunschweigs entire ring road. Autonomous driving on this two-lane urban road includes interaction with traffic, behavior at intersections, lane change maneuvers at speeds up to 60 km/h as well as merging into moving traffic. The demanding terms of the surroundings require an extremely high precision of all modules. Compared to former research activities in autonomous driving, the width of the ring roads roadway varies significantly and has both narrow curves close to the turn radius of the vehicle and straight roads. Therefore, a new approach for trajectory planning having the comprehensive treatment of path-planned sections as its distinctive feature has been realized and the first major success within the context of the “Stadtpilot”-Project. Curvature optimized trajectories are generated over the whole roadway that are independent from the way driving decision are found, resulting in a safe, smooth and comfortable driving behavior. This paper introduces the algorithm and shows its potential on the basis of a typical driving maneuver on the ring road.