TY - INPR A1 - Kruber, Friedrich A1 - Wurst, Jonas A1 - Botsch, Michael T1 - An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization UR - https://doi.org/10.48550/arXiv.2004.02121 Y1 - 2020 UR - https://doi.org/10.48550/arXiv.2004.02121 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Balasubramanian, Lakshman A1 - Kruber, Friedrich A1 - Botsch, Michael A1 - Deng, Ke T1 - Open-Set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios T2 - 2021 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV48863.2021.9575433 Y1 - 2021 UR - https://doi.org/10.1109/IV48863.2021.9575433 SN - 978-1-7281-5394-0 SP - 674 EP - 681 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kruber, Friedrich A1 - Wurst, Jonas A1 - Botsch, Michael T1 - An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization T2 - 2018 IEEE Intelligent Transportation Systems Conference UR - https://doi.org/10.1109/ITSC.2018.8569682 Y1 - 2018 UR - https://doi.org/10.1109/ITSC.2018.8569682 SN - 978-1-7281-0323-5 SP - 2811 EP - 2818 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Sánchez Morales, Eduardo A1 - Kruber, Friedrich A1 - Botsch, Michael A1 - Huber, Bertold A1 - García Higuera, Andres T1 - Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery T2 - 2020 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV47402.2020.9304705 Y1 - 2021 UR - https://doi.org/10.1109/IV47402.2020.9304705 SN - 978-1-7281-6673-5 SP - 2081 EP - 2088 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Kruber, Friedrich A1 - Sánchez Morales, Eduardo A1 - Egolf, Robin A1 - Wurst, Jonas A1 - Chakraborty, Samarjit A1 - Botsch, Michael T1 - Micro- and Macroscopic Road Traffic Analysis using Drone Image Data JF - Leibniz Transactions on Embedded Systems N2 - The current development in the drone technology, alongside with machine learning based image processing, open new possibilities for various applications. Thus, the market volume is expected to grow rapidly over the next years. The goal of this paper is to demonstrate the capabilities and limitations of drone based image data processing for the purpose of road traffic analysis. In the first part a method for generating microscopic traffic data is proposed. More precisely, the state of vehicles and the resulting trajectories are estimated. The method is validated by conducting experiments with reference sensors and proofs to achieve precise vehicle state estimation results. It is also shown, how the computational effort can be reduced by incorporating the tracking information into a neural network. A discussion on current limitations supplements the findings. By collecting a large number of vehicle trajectories, macroscopic statistics, such as traffic flow and density can be obtained from the data. In the second part, a publicly available drone based data set is analyzed to evaluate the suitability for macroscopic traffic modeling. The results show that the method is well suited for gaining detailed information about macroscopic statistics, such as traffic flow dependent time headway or lane change occurrences. In conclusion, this paper presents methods to exploit the remarkable opportunities of drone based image processing for joint macro- and microscopic traffic analysis. UR - https://doi.org/10.4230/LITES.8.1.2 KW - traffic data analysis KW - trajectory data KW - drone image data Y1 - 2022 UR - https://doi.org/10.4230/LITES.8.1.2 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-29704 SN - 2199-2002 VL - 8 IS - 1 SP - 02:1 EP - 02:27 PB - Schloss Dagstuhl CY - Wadern ER - TY - INPR A1 - Kruber, Friedrich A1 - Wurst, Jonas A1 - Botsch, Michael A1 - Chakraborty, Samarjit T1 - Highway traffic data: macroscopic, microscopic and criticality analysis for capturing relevant traffic scenarios and traffic modeling based on the highD data set UR - https://doi.org/10.48550/arXiv.1903.04249 KW - Time-To-Collision KW - Time-Headway KW - Risk Perception KW - traffic stream KW - traffic density KW - traffic flow rate KW - driver behavior KW - traffic simulation KW - highway traffic KW - highD Y1 - 2019 UR - https://doi.org/10.48550/arXiv.1903.04249 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Kruber, Friedrich A1 - Wurst, Jonas A1 - Botsch, Michael A1 - Chakraborty, Samarjit ED - Kukkala, Vipin Kumar ED - Pasricha, Sudeep T1 - Unsupervised Random Forest Learning for Traffic Scenario Categorization T2 - Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems UR - https://doi.org/10.1007/978-3-031-28016-0_20 KW - Random forest KW - Unsupervised learning KW - Traffic scenarios KW - Categorization and clustering Y1 - 2023 UR - https://doi.org/10.1007/978-3-031-28016-0_20 SN - 978-3-031-28016-0 SN - 978-3-031-28015-3 SP - 565 EP - 590 PB - Springer CY - Cham ER - TY - CHAP A1 - Kruber, Friedrich A1 - Wurst, Jonas A1 - Sánchez Morales, Eduardo A1 - Chakraborty, Samarjit A1 - Botsch, Michael T1 - Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification T2 - 2019 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IVS.2019.8813994 Y1 - 2019 UR - https://doi.org/10.1109/IVS.2019.8813994 SN - 978-1-7281-0560-4 SP - 2463 EP - 2470 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Kruber, Friedrich A1 - Sánchez Morales, Eduardo A1 - Chakraborty, Samarjit A1 - Botsch, Michael T1 - Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles T2 - 2020 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV47402.2020.9304794 Y1 - 2021 UR - https://doi.org/10.1109/IV47402.2020.9304794 SN - 978-1-7281-6673-5 SP - 2089 EP - 2096 PB - IEEE CY - Piscataway ER - TY - INPR A1 - Kruber, Friedrich A1 - Sánchez Morales, Eduardo A1 - Chakraborty, Samarjit A1 - Botsch, Michael T1 - Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles UR - https://doi.org/10.48550/arXiv.2004.08206 Y1 - 2020 UR - https://doi.org/10.48550/arXiv.2004.08206 PB - arXiv CY - Ithaca ER -