Download or read book Probabilistic Maneuver Recognition in Traffic Scenarios written by Firl, Jonas and published by KIT Scientific Publishing. This book was released on 2015-01-07 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Probabilistic Maneuver Recognition in Traffic Scenarios written by Jonas Firl and published by . This book was released on 2020-10-09 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Novel Aggregated Solutions for Robust Visual Tracking in Traf c Scenarios written by Tian, Wei and published by KIT Scientific Publishing. This book was released on 2019-05-21 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Probabilistic Motion Planning for Automated Vehicles written by Naumann, Maximilian and published by KIT Scientific Publishing. This book was released on 2021-02-25 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Computational Intelligence written by Juan Julian Merelo and published by Springer. This book was released on 2018-10-03 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Characterizing the Safety of Automated Vehicles written by Juan Pimentel and published by SAE International. This book was released on 2019-03-07 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Proceedings 26 Workshop Computational Intelligence Dortmund 24 25 November 2016 written by Hoffmann, Frank and published by KIT Scientific Publishing. This book was released on 2016-11-14 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Motion Planning for Autonomous Vehicles in Partially Observable Environments written by Taş, Ömer Şahin and published by KIT Scientific Publishing. This book was released on 2023-10-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Belief State Planning for Autonomous Driving Planning with Interaction Uncertain Prediction and Uncertain Perception written by Hubmann, Constantin and published by KIT Scientific Publishing. This book was released on 2021-09-13 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Self Calibration of Multi Camera Systems for Vehicle Surround Sensing written by Knorr, Moritz and published by KIT Scientific Publishing. This book was released on 2018-12-19 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Omnidirectional Stereo Vision for Autonomous Vehicles written by Schoenbein, Miriam and published by KIT Scientific Publishing. This book was released on 2015-04-22 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environment perception with cameras is an important requirement for many applications for autonomous vehicles and robots. This work presents a stereoscopic omnidirectional camera system for autonomous vehicles which resolves the problem of a limited field of view and provides a 360° panoramic view of the environment. We present a new projection model for these cameras and show that the camera setup overcomes major drawbacks of traditional perspective cameras in many applications.

Download or read book Lane Precise Localization with Production Vehicle Sensors and Application to Augmented Reality Navigation written by Rabe, Johannes and published by KIT Scientific Publishing. This book was released on 2019-01-10 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This works describes an approach to lane-precise localization on current digital maps. A particle filter fuses data from production vehicle sensors, such as GPS, radar, and camera. Performance evaluations on more than 200 km of data show that the proposed algorithm can reliably determine the current lane. Furthermore, a possible architecture for an intuitive route guidance system based on Augmented Reality is proposed together with a lane-change recommendation for unclear situations.

Download or read book Integrated Planning and Control for Collision Avoidance Systems written by Yi, Boliang and published by KIT Scientific Publishing. This book was released on 2018-08-29 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mobile laser scanning based determination of railway network topology and branching direction on turnouts written by Stein, Denis and published by KIT Scientific Publishing. This book was released on 2018-06-26 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Compact Environment Modelling from Unconstrained Camera Platforms written by Schwarze, Tobias and published by KIT Scientific Publishing. This book was released on 2018-09-25 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fusion of Data from Heterogeneous Sensors with Distributed Fields of View and Situation Evaluation for Advanced Driver Assistance Systems written by Otto, Carola and published by KIT Scientific Publishing. This book was released on 2014-07-29 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to develop a driver assistance system for pedestrian protection, pedestrians in the environment of a truck are detected by radars and a camera and are tracked across distributed fields of view using a Joint Integrated Probabilistic Data Association filter. A robust approach for prediction of the system vehicles trajectory is presented. It serves the computation of a probabilistic collision risk based on reachable sets where different sources of uncertainty are taken into account.

Download or read book Safe Intention aware Maneuvering of Autonomous Vehicles written by Xin Cyrus Huang and published by . This book was released on 2019 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to improve driving performance, while achieving safety in a dynamic environment, it is crucial for a vehicle motion planner to be aware of the intentions of the surrounding agent vehicles. Many existing approaches that ignore the intentions of surrounding vehicles would produce risky or over-conservative plans. In this thesis, we describe a maneuver motion planning system that achieves both safety and efficiency by estimating the types of surrounding drivers and the vehicle motions being executed by them over a finite horizon in the future. Our claim is that a vehicle is able to efficiently and safely navigate in dynamic traffic situations by estimating the possible types of drivers in its immediate vicinity, such as aggressive or careful, and by predicting their likely maneuvers and motions as probability distributions. To perform these predictions, we first employ a vehicle model that incorporates different driving styles, possible types of maneuvers, the likely trajectories that these maneuvers produce, and the likelihood of transitioning between successive maneuvers. The vehicle models are combined and encoded as hybrid partially observable Markov decision processes (POMDPs) whose discrete elements represent driving styles and maneuvers for each style and whose continuous parts represent vehicle motions. We then frame the problem of recognizing a vehicle's current driving style and maneuver as a belief state update on the hybrid POMDP. The driving style is assessed using multinomial logistic regression classification, while the maneuver is estimated using Bayesian filtering over a variant of probabilistic hybrid automata and a library of pre-learned motion primitive models. Multinomial logistic regression classification allows us to predict driving styles probabilistically using multiple driving features, and Bayesian filtering provides robust estimation results based on the prior information. Given the recognition results and the learned motion primitive models, we provide probabilistically sound predictions of the future maneuver and trajectory sequence of each agent vehicle. Finally, we compute safe motion plans of the ego vehicle in light of recognized agent vehicle driver styles, intended maneuvers, and future vehicle trajectories, by performing risk-bounded planning on the hybrid POMDP model. We demonstrate our system in a number of challenging simulated environments, including unprotected intersection left turns and lane changes with multiple dynamic vehicles. The demonstration shows that our intent recognition algorithms achieve an average driving style estimation accuracy of 89.89%, an average maneuver estimation accuracy of 98.9%, and an average trajectory prediction error of 2.12 meters. Furthermore, our maneuver planning system guarantees safety with respect to the safety constraint, while arriving at the goal 13.71% faster compared to a state-of-the-art planner without the intent recognition capability.