Martin Liebner

Driver intent inference at urban intersections using the intelligent driver model

Predicting turn and stop maneuvers of potentially errant drivers is a basic requirement for advanced driver assistance systems for urban intersections. Previous work has shown that an early estimate of the drivers intent can be inferred by evaluating the vehicles speed during the intersection approach. In the presence of a preceding vehicle, however, the velocity profile might be dictated by car-following behaviour rather than by the need to slow down before doing a left or right turn. To infer the drivers intent under such circumstances, a simple, real-time capable approach using an explicit model to represent both car-following and turning behaviour is proposed. Models for typical turning behavior are extracted from real world data. Preliminary results based on a Bayes net classification are presented.

Velocity-Based Driver Intent Inference at Urban Intersections in the Presence of Preceding Vehicles

Predicting turn and stop maneuvers of potentially errant drivers is a basic requirement for advanced driver assistance systems for urban intersections. Previous work has shown that an early estimate of the drivers intent can be inferred by evaluating the vehicles speed during the intersection approach. In the presence of a preceding vehicle, however, the velocity profile might be dictated by car-following behavior rather than by the need to slow down before doing a left or right turn. To infer the drivers intent under such circumstances, a simple, real-time capable approach using a parametric model to represent both car-following and turning behavior is proposed. The performance of two alternative parameterizations based on observations at an individual intersection and a generic curvature-based model is evaluated in combination with two different Bayes net classification algorithms. In addition, the driver model is shown to be capable of predicting the future trajectory of the vehicle.

Active safety for vulnerable road users based on smartphone position data

Smartphones have long become an omnipresent part of our life. Equipped with both a broadband internet connection and advanced GPS onboard sensors, the idea is to use them as mobile sensors for active safety systems that aim at protecting vulnerable road users such as pedestrians or cyclists. This paper gives a comprehensive analysis of todays smartphones GPS accuracy on an inner-city bicycle track. In addition, the transmission latencies of a prototypical bicycle warning system are evaluated. The results show that while the lateral deviations are still too high to allow for lane-level localization, the longitudinal accuracy as well as the transmission latencies are good enough for many active safety applications already.

Generic driver intent inference based on parametric models

Reasoning about the driver intent is fundamental both to advanced driver assistance systems as well as to highly automated driving. In contrast to the vast majority of preceding work, we investigate an architecture that can deal with arbitrary combinations of subsequent maneuvers as well as a varying set of available features. Detailed parametric models are given for the indicator, velocity and gaze direction features, all of which are parametrized from the results of extensive user studies. Evaluation is carried out for continuous right-turn prediction on a separate data set. Assuming conditional independence between the individual feature likelihoods, we investigate the contribution of each feature to the overall classification result separately. In particular, the approach is shown to work well even when faced with implausible observations of the indicator feature.

Fahrerabsichtserkennung und Risikobewertung

Obwohl die Zahl der Verkehrstoten in den letzten Jahrzehnten standig zuruckgegangen ist und 2013 mit 3340 Toten einen neuen historischen Tiefstand erreichte [1], besteht nach wie vor die Notwendigkeit, diese auch in Zukunft weiter zu reduzieren. Entsprechende Zielsetzungen kommen hierbei sowohl von europaischer Seite [2] wie auch von Seiten der Bundesregierung [3]. Neben strasenbaulichen Masnahmen und der Verbesserung des Insassenschutzes sind insbesondere auch Fahrerassistenzsysteme in der Lage, hierzu einen wesentlichen Beitrag zu leisten. Wahrend fruhe Systeme wie ABS und ESC auf die Unterstutzung der Fahrzeugsteuerung beschrankt waren, existieren mittlerweile eine Vielzahl von Fahrerassistenzsystemen, die den Fahrer aktiv auf bestehende Gefahren hinweisen und es ihm dadurch ermoglichen, einen Grosteil der Unfalle zu verhindern [4].