scholarly journals Optimization of AUTOSAR Communication Stack in the Context of Advanced Driver Assistance Systems

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4561
Author(s):  
Răzvan Bogdan ◽  
Mihaela Crișan-Vida ◽  
Darius Barmayoun ◽  
Loredana Lavinia Staicu ◽  
Robert Valentin Puiu ◽  
...  

New trends in the automotive industry such as autonomous driving and Car2X require a large amount of data to be exchanged between different devices. Radar sensors are key components in developing vehicles of the future, therefore these devices are used in a large spectrum of applications, where data traffic is of paramount importance. As a result, communication traffic volumes have become more complex, leading to the research of optimization approaches to be applied at the AUTOSAR level. Our paper offers such an optimization solution at the AUTOSAR communication level. The radar sensor is accessed in a remote manner, and the experiments aimed at performance measurements revealed that our solution is superior to the Full AUTOSAR implementation in terms of memory usage and runtime measurements.

Author(s):  
Mike Köhler ◽  
Jürgen Hasch ◽  
Hans Ludwig Blöcher ◽  
Lorenz-Peter Schmidt

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.


2021 ◽  
Vol 69 (6) ◽  
pp. 511-523
Author(s):  
Henrietta Lengyel ◽  
Viktor Remeli ◽  
Zsolt Szalay

Abstract The emergence of new autonomous driving systems and functions – in particular, systems that base their decisions on the output of machine learning subsystems responsible for environment perception – brings a significant change in the risks to the safety and security of transportation. These kinds of Advanced Driver Assistance Systems are vulnerable to new types of malicious attacks, and their properties are often not well understood. This paper demonstrates the theoretical and practical possibility of deliberate physical adversarial attacks against deep learning perception systems in general, with a focus on safety-critical driver assistance applications such as traffic sign classification in particular. Our newly developed traffic sign stickers are different from other similar methods insofar that they require no special knowledge or precision in their creation and deployment, thus they present a realistic and severe threat to traffic safety and security. In this paper we preemptively point out the dangers and easily exploitable weaknesses that current and future systems are bound to face.


2020 ◽  
Vol 25 (3) ◽  
pp. 83-92
Author(s):  
Bong-Seo Park ◽  
Hyun-cheol Park ◽  
Jung-jun Her

With the development of advanced driver assistance systems, the more reliable the autonomous driving technology is, the more the rest and entertainment times of the driver of the car increases. Hence, the importance of the entertainment function of automotive audio-video navigation (AVN) systems is increasing. Currently, the AVN system of automobiles has a monitoring function for fault diagnosis and a combination of functions. Applying these technologies is challenging for drivers who want to tune the audio quality to their musical taste. In this study, a method for upgrading the sound quality using a power supply noise filter without deforming the AVN system was developed. The low-pass attenuation that appeared as a side effect was solved by applying a filter using the loudness isotropic curve. In the installation method of the filter, the method of using a fuse holder minimized the inconvenience of AVN detachment and wiring. Based on the results obtained in this study, further research and improvement of the filter are required for audio tuning of various models.


2012 ◽  
Vol 2012 (CICMT) ◽  
pp. 000077-000081
Author(s):  
Sebastian Brunner ◽  
Manfred Stadler ◽  
Xin Wang ◽  
Frank Bauer ◽  
Klaus Aichholzer

In this paper we will present an application of advanced Low Temperature Cofired Ceramic (LTCC) technology beyond 60 GHz. Therefore a RF frontend for 76–81 GHz radar frequency was built. LTCC is a well established technology for applications for consumer handheld units <5 GHz but will provide solutions for applications for high frequencies in the range of 60 GHz and beyond. Radar sensors operating in the 76-81 GHz range are considered key for Advanced Driver Assistance Systems (ADAS) like Adaptive Cruise Control (ACC), Collision Mitigation and Avoidance Systems (CMS) or Lane Change Assist (LCA). These applications are the next wave in automotive safety systems and have thus generated increased interest in lower-cost solutions especially for the mm-wave frontend section.


Author(s):  
Julia Orlovska ◽  
Fjolle Novakazi ◽  
Casper Wickman ◽  
Rikard Soderberg

AbstractAutomotive systems are changing rapidly from purely mechanical to smart, programmable assistants. These systems react and respond to the driving environment and communicate with other subsystems for better driver support and safety. However, instead of supporting, the complexity of such systems can result in a stressful experience for the driver, adding to the workload. Hence, a poorly designed system, from a usability and user experience perspective, can lead to reduced usage or even ignorance of the provided functionalities, especially concerning Adaptive Driver Assistance Systems.In this paper, the authors propose a combined design approach for user behavior evaluation of such systems. At the core of the design is a mixed methods approach, where objective data, which is automatically collected in vehicles, is augmented with subjective data, which is gathered through in- depth interviews with end-users. The aim of the proposed methodology design is to improve current practices on user behavior evaluation, achieve a deeper understanding of driver's behavior, and improve the validity and rigor of the named results.


Author(s):  
Raik Schnabel ◽  
Raphael Hellinger ◽  
Dirk Steinbuch ◽  
Joachim Selinger ◽  
Michael Klar ◽  
...  

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.


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