Probabilistic Maneuver Recognition in Traffic Scenarios
Probabilistic Maneuver Recognition in Traffic Scenarios

Author: Firl, Jonas

Publisher: KIT Scientific Publishing

Published: 2015-01-07

Total Pages: 176

ISBN-13: 3731502879

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In this work an approach is presented to model and recognize traffic maneuvers in terms of interactions between different traffic participants on extra urban roads. Results of the recognition concept are presented and evaluated using different sensor setups and its benefit is outlined by an integration into a software framework in the field of Car-to-Car (C2C) communications. Furthermore, recognition results are used in this work to robustly predict vehicle's trajectories while driving dynamic.

Probabilistic Maneuver Recognition in Traffic Scenarios
Probabilistic Maneuver Recognition in Traffic Scenarios

Author: Jonas Firl

Publisher:

Published: 2020-10-09

Total Pages: 166

ISBN-13: 9781013283734

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In this work an approach is presented to model and recognize traffic maneuvers in terms of interactions between different traffic participants on extra urban roads. Results of the recognition concept are presented and evaluated using different sensor setups and its benefit is outlined by an integration into a software framework in the field of Car-to-Car (C2C) communications. Furthermore, recognition results are used in this work to robustly predict vehicle's trajectories while driving dynamic This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Novel Aggregated Solutions for Robust Visual Tracking in Traffic Scenarios
Novel Aggregated Solutions for Robust Visual Tracking in Traffic Scenarios

Author: Tian, Wei

Publisher: KIT Scientific Publishing

Published: 2019-05-21

Total Pages: 178

ISBN-13: 3731509156

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This work proposes novel approaches for object tracking in challenging scenarios like severe occlusion, deteriorated vision and long range multi-object reidenti?cation. All these solutions are only based on image sequence captured by a monocular camera and do not require additional sensors. Experiments on standard benchmarks demonstrate an improved state-of-the-art performance of these approaches. Since all the presented approaches are smartly designed, they can run at a real-time speed.

Probabilistic Motion Planning for Automated Vehicles
Probabilistic Motion Planning for Automated Vehicles

Author: Naumann, Maximilian

Publisher: KIT Scientific Publishing

Published: 2021-02-25

Total Pages: 192

ISBN-13: 3731510707

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In motion planning for automated vehicles, a thorough uncertainty consideration is crucial to facilitate safe and convenient driving behavior. This work presents three motion planning approaches which are targeted towards the predominant uncertainties in different scenarios, along with an extended safety verification framework. The approaches consider uncertainties from imperfect perception, occlusions and limited sensor range, and also those in the behavior of other traffic participants.

Computational Intelligence
Computational Intelligence

Author: Juan Julian Merelo

Publisher: Springer

Published: 2018-10-03

Total Pages: 306

ISBN-13: 331999283X

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This book gathers revised and extended versions of the best papers presented at the 8th International Joint Conference on Computational Intelligence (IJCCI 2016), which was held in Porto, Portugal from 9 to 11 November 2016. The papers address three main fields of Computational Intelligence, namely: Evolutionary Computation, Fuzzy Computation, and Neural Computation. In addition to highlighting recent advances in these areas, the book offers veteran researchers new and innovative solutions, while also providing a source of information and inspiration for newcomers to the field.

Characterizing the Safety of Automated Vehicles
Characterizing the Safety of Automated Vehicles

Author: Juan Pimentel

Publisher: SAE International

Published: 2019-03-07

Total Pages: 190

ISBN-13: 0768002109

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Safety has been ranked as the number one concern for the acceptance and adoption of automated vehicles since safety has driven some of the most complex requirements in the development of self-driving vehicles. Recent fatal accidents involving self-driving vehicles have uncovered issues in the way some automated vehicle companies approach the design, testing, verification, and validation of their products. Traditionally, automotive safety follows functional safety concepts as detailed in the standard ISO 26262. However, automated driving safety goes beyond this standard and includes other safety concepts such as safety of the intended functionality (SOTIF) and multi-agent safety. Characterizing the Safety of Automated Vehicles addresses the concept of safety for self-driving vehicles through the inclusion of 10 recent and highly relevent SAE technical papers. Topics that these papers feature include functional safety, SOTIF, and multi-agent safety. As the first title in a series on automated vehicle safety, each will contain introductory content by the Editor with 10 SAE technical papers specifically chosen to illuminate the specific safety topic of that book.

Motion Planning for Autonomous Vehicles in Partially Observable Environments
Motion Planning for Autonomous Vehicles in Partially Observable Environments

Author: Taş, Ömer Şahin

Publisher: KIT Scientific Publishing

Published: 2023-10-23

Total Pages: 222

ISBN-13: 3731512998

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This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.

Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception
Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception

Author: Hubmann, Constantin

Publisher: KIT Scientific Publishing

Published: 2021-09-13

Total Pages: 178

ISBN-13: 3731510391

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This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consider the prediction uncertainty (e.g. different intentions), perception uncertainty (e.g. occlusions) as well as the uncertain interactive behavior of the other agents explicitly. Simulating the most likely future scenarios allows to find an optimal policy online that enables non-conservative planning under uncertainty.

Self-Calibration of Multi-Camera Systems for Vehicle Surround Sensing
Self-Calibration of Multi-Camera Systems for Vehicle Surround Sensing

Author: Knorr, Moritz

Publisher: KIT Scientific Publishing

Published: 2018-12-19

Total Pages: 166

ISBN-13: 373150765X

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Multi-camera systems are being deployed in a variety of vehicles and mobile robots today. To eliminate the need for cost and labor intensive maintenance and calibration, continuous self-calibration is highly desirable. In this book we present such an approach for self-calibration of multi-Camera systems for vehicle surround sensing. In an extensive evaluation we assess our algorithm quantitatively using real-world data.