TY - CHAP A1 - Köhler, Sebastian A1 - Goldhammer, Michael A1 - Zindler, Klaus A1 - Doll, Konrad A1 - Dietmayer, Klaus T1 - Stereo-Vision-Based Pedestrian's Intention Detection in a Moving Vehicle T2 - Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on N2 - We present a method to detect starting, stopping and bending in intentions of pedestrians from a moving vehicle based on stereo-vision. The method focuses on urban scenarios where these pedestrian movements are common and may result in critical situations. Pedestrian intentions are determined by means of an image-based motion contour histogram of oriented gradient descriptor. It is based on silhouettes gathered from stereo data and does not require any compensation of appearance changes resulting from the ego-motion of a vehicle. Nevertheless, it covers small movements indicating a pedestrian’s intention. A linear support vector machine with probabilistic estimates is used for classification. We evaluated our method on the publicly available Daimler Pedestrian Path Prediction Benchmark Dataset containing detections of a stateof-the-art pedestrian detector. We detect a pedestrian’s stopping intention from 125 ms to 500 ms before standing still within an accuracy range of 80% to 100%. Bending in is detected from 320 ms to 570 ms after a first visible lateral body movement in the same accuracy range. The intention to cross the road from standing still (starting) is detected 250 ms after the first visible motion and, therefore, within the first step with an accuracy of 100%. KW - Image Motion Analysis KW - Stereo Image Processing KW - Pedestrian Safety KW - Bildfolgenanalyse Y1 - 2015 U6 - https://doi.org/10.1109/ITSC.2015.374 SP - 2317 EP - 2322 ER - TY - JOUR A1 - Köhler, Sebastian A1 - Goldhammer, Michael A1 - Bauer, Sebastian A1 - Zecha, Stephan A1 - Doll, Konrad A1 - Brunsmann, Ulrich A1 - Dietmayer, Klaus T1 - Stationary Detection of the Pedestrian's Intention at Intersections JF - IEEE Intelligent Transportation Systems Magazine KW - Fahrerassistenzsystem KW - Fußgänger Y1 - 2013 SN - 1939-1390 VL - 2013 IS - 5 SP - 87 EP - 99 ER - TY - JOUR A1 - Goldhammer, Michael A1 - Köhler, Sebastian A1 - Zernetsch, Stefan A1 - Doll, Konrad A1 - Sick, Bernhard A1 - Dietmayer, Klaus T1 - Intentions of Vulnerable Road Users – Detection and Forecasting by Means of Machine Learning JF - IEEE Transactions on Intelligent Transportation Systems KW - Fahrerassistenzsystem KW - Fußgänger KW - Radfahrer Y1 - 2019 UR - https://doi.org/10.1109/TITS.2019.2923319 U6 - https://doi.org/10.1109/TITS.2019.2923319 VL - 2020 IS - 21 / 7 SP - 3035 EP - 3045 ER - TY - CHAP A1 - Seeliger, Florian A1 - Weidl, Galia A1 - Petrich, Dominik A1 - Naujoks, Frederik A1 - Breuel, Gabi A1 - Neukum, Alexandra A1 - Dietmayer, Klaus T1 - Advisory warnings based on cooperative perception T2 - IEEE Intelligent Vehicles Symposium Proceedings, June 2014 N2 - The Ko-PER (cooperative perception) research project aims at improvements of active traffic safety through cooperative perception systems. Within the project a prototype of a cooperative warning system was realized. This system provides early advisory warnings which are especially useful in critical situations with occluded conflict partners. The development process was accompanied by a series of driving simulator studies to determine both the potential to reduce traffic conflicts and important design characteristics of early advisory warning signals. The most important details of the prototype system's components inter-vehicle information-fusion and situation analysis are described and the achieved warning timings are compared to the results of the driving simulator studies. KW - ITS (Intelligent Transportation Systems) KW - Artificial Intelligence KW - Fahrerassistenzsystem Y1 - 2014 UR - https://www.researchgate.net/publication/264732322_Advisory_warnings_based_on_cooperative_perception#fullTextFileContent U6 - https://doi.org/10.1109/IVS.2014.6856479 ER - TY - CHAP A1 - Köhler, Sebastian A1 - Goldhammer, Michael A1 - Bauer, Sebastian A1 - Doll, Konrad A1 - Brunsmann, Ulrich A1 - Dietmayer, Klaus T1 - Early Detection of the Pedestrian’s Intention to Cross the Street T2 - 15th International IEEE Conference on Intelligent Transportation Systems (ITSC 2012), Anchorage, Alaska, USA. KW - Fahrerassistenzsystem KW - Bildverarbeitung Y1 - 2012 UR - http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2012/Koehler12-EDO.pdf U6 - https://doi.org/10.1109/ITSC.2012.6338797 SP - 1759 EP - 1764 ER - TY - CHAP A1 - Goldhammer, Michael A1 - Strigel, Elias A1 - Meissner, Daniel A1 - Brunsmann, Ulrich A1 - Doll, Konrad A1 - Dietmayer, Klaus T1 - Cooperative Multi Sensor Network for Traffic Safety Applications at Intersections T2 - 15th International IEEE Conference on Intelligent Transportation Systems (ITSC 2012), Anchorage, Alaska, USA. KW - Fahrerassistenzsystem KW - Bildverarbeitung Y1 - 2012 U6 - https://doi.org/10.1109/ITSC.2012.6338672 SP - 1178 EP - 1183 ER -