Due to its robust operation and high performance during bad weather conditions and overnight as well as the ability of using the Doppler Effect to measure directly the velocity of objects, the radar sensor is used in many application fields. Especially in automotive many radar sensors are used for the perception of the environment to increase the safety of the traffic. To increase the security level especially for vulnerable road users (VRU’s) like pedestrians or cyclists, radar sensors are used in driver assistance systems. Radar sensors are also used in the infrastructure, e.g. a commercial application is the detection of cars and pedestrians to manage traffic lights. Furthermore, radar sensors installed in the infrastructure are used in research projects for safeguarding future autonomous traffic. The object recognition and accuracy of radar-based sensing in the infrastructure can be increased by cooperating radar systems, which consist out of several sensors. This paper focus on the data fusion method of two radar sensors to increase the performance of detection and localization. For data fusion the high level cluster data of the two radar sensors are used as input data in a neuronal net (NN) structure. The results are compared to the localization obtained by using only a single radar sensor operating with an ordinary tracking algorithm. First, different models for chosen region of interests (ROI) and operating mode of cooperative sensors are developed and the data structure is discussed. In addition, the data are preprocessed with a coordinate transformation and time synchronization for both sensors, as well as the noise filtering to reduce the amount of clusters for the algorithm. Furthermore, three NN structures (CNN, DNN and LSTM) for static + dynamic objects and only dynamic objects are created, trained and discussed. Also, based on the results further improvements for the NN performance will be discussed.
Mr. Egor Streck, Technische Hochschule Ingolstadt, GERMANY Dipl.-Ing. Peter Schmok, ADC Automotive Distance Control Systems GmbH (Continental), GERMANY Dr. Klaus Schneider, Conti Themic microelectronic GmbH, GERMANY Dr.-Ing. Hueseyin Erdogan, Conti Themic microelectronic GmbH, GERMANY Prof. Dr. Gordon Elger, Fraunhofer-Institut für Verkehrs- und Infrastruktursysteme IVI, GERMANY
Safeguarding Future Autonomous Traffic by Infrastructure based on Multi Radar Sensor Systems
F2021-ACM-121 • Paper + Video • FISITA World Congress 2021 • ACM - Automated and Connected Mobility
Upgrade your ICC subscription to access all Library items.
Congratulations! Your ICC subscription gives you complete access to the FISITA Library.
Retrieving info...
Available for purchase on the FISITA Store
OR