Search results for: Stefan Klingelschmitt
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This work addresses two topics. On one hand we study the problem of general measures for spatio-temporal trajectory similarity based on the evaluation of longitudinal and lateral spatio-temporal distance. On the other hand we employ trajectory similarity measures to general situation classification problems for traffic scenarios, which include the well-known problem of lane assignment and driving...
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Future advanced driver assistance systems as well as autonomous vehicles are expected to further increase their areas of applicability. Reliable maneuver estimations are a prerequisite for many of the intended functionalities. Accordingly, maneuver estimation systems need to cover a wide range of scenarios. The majority of recently presented approaches are targeted at fixed scenarios. However, having...
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2016 IEEE Intelligent Vehicles Symposium (IV) > 1141 - 1148
Situation recognition is a prerequisite for many advanced driver assistance systems as well as for partially and fully automated vehicles. Current situation recognition approaches focus mainly on estimating maneuvers of single scene entities. However, assessing multiple, possibly interacting, traffic participants simultaneously is crucial in complex traffic scenes and has hardly been investigated...
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Intersections are among the most accident prone spots in traffic. Future Advanced Driver Assistance Systems (ADAS) are aiming to assist the driving task in these complex scenarios. This can be realized by assessing the criticality of possible occurring situations. For such criticality assessment techniques predicting the trajectories of the involved traffic participants several seconds in advance...
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2015 IEEE Intelligent Vehicles Symposium (IV) > 1232 - 1239
Due to the large number and the high variability of possible traffic situations, intersections are among the most accident-prone spots in inner-city traffic. To reliably assist the driving tasks elaborated risk assessment systems are needed. Current approaches are mainly based on the prediction of possible future trajectories of the involved traffic participants. However, considering the variability...
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2015 IEEE Intelligent Vehicles Symposium (IV) > 322 - 329
The Intelligent Driver Model (IDM) is a microscopic, time continuous car following model for the simulation of freeway and urban traffic. Its popularity is grounded in its simplicity and its capacity to describe both single vehicle velocity profiles as well as collective traffic behavior. Nevertheless, it lacks a series of properties that would be desirable for more realistic agent models. In this...
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Intersections are the most accident-prone spots in the road network. In order to assist the driver in complex urban intersection situations, an ADAS will be required not only to recognize current but also to anticipate future maneuvers of the involved road users. Current approaches for intention estimation focus mainly on discerning only two intentions based on a vehicle's behavior. We argue that...
