scholarly journals Virtual sensor models for real-time applications

2016 ◽  
Vol 14 ◽  
pp. 31-37 ◽  
Author(s):  
Nils Hirsenkorn ◽  
Timo Hanke ◽  
Andreas Rauch ◽  
Bernhard Dehlink ◽  
Ralph Rasshofer ◽  
...  
Keyword(s):  
Real Time ◽  
Statistical Data ◽  
Position Estimation ◽  
Data Driven ◽  
Driver Assistance ◽  
Automotive Radar ◽  
Driver Assistance Systems ◽  
Sensor Model ◽  
Sensor Models ◽  
Assistance Systems

Abstract. Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

scholarly journals Feasibility of automotive radar at frequencies beyond 100 GHz

2012 ◽  
Vol 5 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Mike Köhler ◽  
Jürgen Hasch ◽  
Hans Ludwig Blöcher ◽  
Lorenz-Peter Schmidt
Keyword(s):  
Angular Resolution ◽  
Frequency Regulation ◽  
Driver Assistance ◽  
Automotive Radar ◽  
Driver Assistance Systems ◽  
Radar Sensors ◽  
Miniaturized Antenna ◽  
High Resolution Radar ◽  
Assistance Systems ◽  
Operation Frequency

Radar sensors are used widely in modern driver assistance systems. Available sensors nowadays often operate in the 77 GHz band and can accurately provide distance, velocity, and angle information about remote objects. Increasing the operation frequency allows improving the angular resolution and accuracy. In this paper, the technical feasibility to move the operation frequency beyond 100 GHz is discussed, by investigating dielectric properties of radome materials, the attenuation of rain and atmosphere, radar cross-section behavior, active circuits technology, and frequency regulation issues. Moreover, a miniaturized antenna at 150 GHz is presented to demonstrate the possibilities of high-resolution radar for cars.

scholarly journals From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Ushemadzoro Chipengo ◽  
Peter M. Krenz ◽  
Shawn Carpenter
Keyword(s):  
Target Identification ◽  
Pedestrian Detection ◽  
High Fidelity ◽  
Driver Assistance ◽  
Automotive Radar ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Radar Systems ◽  
False Target ◽  
Assistance Systems

Advanced driver assistance systems (ADAS) have recently been thrust into the spotlight in the automotive industry as carmakers and technology companies pursue effective active safety systems and fully autonomous vehicles. Various sensors such as lidar (light detection and ranging), radar (radio detection and ranging), ultrasonic, and optical cameras are employed to provide situational awareness to vehicles in a highly dynamic environment. Radar has emerged as a primary sensor technology for both active/passive safety and comfort-advanced driver-assistance systems. Physically building and testing radar systems to demonstrate reliability is an expensive and time-consuming process. Simulation emerges as the most practical solution to designing and testing radar systems. This paper provides a complete, full physics simulation workflow for automotive radar using finite element method and asymptotic ray tracing electromagnetic solvers. The design and optimization of both transmitter and receiver antennas is presented. Antenna interaction with vehicle bumper and fascia is also investigated. A full physics-based radar scene corner case is modelled to obtain high-fidelity range-Doppler maps. Finally, this paper investigates the effects of inclined roads on late pedestrian detection and the effects of construction metal plate radar returns on false target identification. Possible solutions are suggested and validated. Results from this study show how pedestrian radar returns can be increased by over 16 dB for early detection along with a 27 dB reduction in road construction plate radar returns to suppress false target identification. Both solutions to the above corner cases can potentially save pedestrian lives and prevent future accidents.

scholarly journals THE USE OF VEHICLE DATA IN ADAS DEVELOPMENT, VERIFICATION AND FOLLOW-UP ON THE SYSTEM

2020 ◽  
Vol 1 ◽  
pp. 2551-2560
Author(s):  
J. Orlovska ◽  
C. Wickman ◽  
R. Soderberg
Keyword(s):  
Data Driven ◽  
Context Aware ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Volvo Cars ◽  
Vehicle Data ◽  
Assistance Systems ◽  
High Level

AbstractAdvanced Driver Assistance Systems (ADAS) require a high level of interaction between the driver and the system, depending on driving context at a particular moment. Context-aware ADAS evaluation based on vehicle data is the most prominent way to assess the complexity of ADAS interactions. In this study, we conducted interviews with the ADAS development team at Volvo Cars to understand the role of vehicle data in the ADAS development and evaluation. The interviews’ analysis reveals strategies for improvement of current practices for vehicle data-driven ADAS evaluation.

Development of a mid range automotive radar sensor for future driver assistance systems

2013 ◽  
Vol 5 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Raik Schnabel ◽  
Raphael Hellinger ◽  
Dirk Steinbuch ◽  
Joachim Selinger ◽  
Michael Klar ◽  
...  
Keyword(s):  
Silicon Germanium ◽  
Urban Environments ◽  
Planar Antennas ◽  
Driver Assistance ◽  
Automotive Radar ◽  
Driver Assistance Systems ◽  
Radar Sensors ◽  
Assistance Systems ◽  
On Chip ◽  
Safety Applications

Radar sensors are key components of modern driver assistance systems. The application of such systems in urban environments for safety applications is the primary goal of the project “Radar on Chip for Cars” (RoCC). Major outcomes of this project will be presented and discussed in this contribution. These outcomes include the specification of radar sensors for future driver assistance systems, radar concepts, and integration technologies for silicon-germanium (SiGe) MMICs, as well as the development and evaluation of a system demonstrator. A radar architecture utilizing planar antennas and highly integrated components will be proposed and discussed with respect to system specifications. The developed system demonstrator will be evaluated in terms of key parameters such as field of view, distance, and angular separability. Finally, as an outlook a new mid range radar (MRR) will be introduced incorporating several concepts and technologies developed in this project.

scholarly journals Moving Object Detection Based on Optical Flow Estimation and a Gaussian Mixture Model for Advanced Driver Assistance Systems

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3217 ◽  
Author(s):  
Jaechan Cho ◽  
Yongchul Jung ◽  
Dong-Sun Kim ◽  
Seongjoo Lee ◽  
Yunho Jung
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Moving Object Detection ◽  
Moving Object ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Moving Camera ◽  
Real Time Processing ◽  
Time Processing ◽  
Assistance Systems

Most approaches for moving object detection (MOD) based on computer vision are limited to stationary camera environments. In advanced driver assistance systems (ADAS), however, ego-motion is added to image frames owing to the use of a moving camera. This results in mixed motion in the image frames and makes it difficult to classify target objects and background. In this paper, we propose an efficient MOD algorithm that can cope with moving camera environments. In addition, we present a hardware design and implementation results for the real-time processing of the proposed algorithm. The proposed moving object detector was designed using hardware description language (HDL) and its real-time performance was evaluated using an FPGA based test system. Experimental results demonstrate that our design achieves better detection performance than existing MOD systems. The proposed moving object detector was implemented with 13.2K logic slices, 104 DSP48s, and 163 BRAM and can support real-time processing of 30 fps at an operating frequency of 200 MHz.

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