scholarly journals Design of a FlexRay/Ethernet Gateway and Security Mechanism for In-Vehicle Networks

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 641 ◽  
Author(s):  
Trong-Yen Lee ◽  
I-An Lin ◽  
Ren-Hong Liao
Keyword(s):  
Communication Protocols ◽  
Security Mechanism ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Main Challenge ◽  
Field Programmable ◽  
High Bandwidth ◽  
Vehicle Networks ◽  
Automotive Networks ◽  
Vehicle Networking

Due to the development of the Internet of Vehicles (IoV) and advanced driver-assistance systems (ADAS), the Ethernet has become one of the most important communication protocols for the future of automotive networks. This is because the existing communication protocols (such as FlexRay) do not provide sufficiently high bandwidth requirements. The main challenge for the automotive industry will be to transfer and extend standard IP and Ethernet into vehicles and still fulfill the automotive requirements. The automotive gateway not only links two or more protocols and exchanges the data using each, but also monitors and ensures functional safety. This paper proposes a FlexRay/Ethernet gateway by considering the development conditions of embedded systems and the security in the field of vehicle networking. The proposed method is implemented on the Field Programmable Gate Array (FPGA) system to evaluate running time and to analyze the overhead of the security mechanism. For one-to-one mapping logic, the execution times of FlexRay to the Ethernet path and Ethernet to FlexRay path are constant, at 4.67 μs and 6.71 μs, respectively. In particular, cybersecurity can be integrated as an extension of the gateway with low latency and power consumption.

scholarly journals Experimental Validation on Intersection Turning Trajectory Prediction Method for Advanced Driver Assistance System Based on Triclothoidal Curve

2021 ◽  
Vol 11 (13) ◽  
pp. 5900
Author(s):  
Yohei Fujinami ◽  
Pongsathorn Raksincharoensak ◽  
Shunsaku Arita ◽  
Rei Kato
Keyword(s):  
Traffic Accidents ◽  
Computational Cost ◽  
Prediction Method ◽  
Smooth Curve ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Trajectory Prediction ◽  
Left Turn ◽  
Left Hand

Advanced driver assistance systems (ADAS) for crash avoidance, when making a right-turn in left-hand traffic or left-turn in right-hand traffic, are expected to further reduce the number of traffic accidents caused by automobiles. Accurate future trajectory prediction of an ego vehicle for risk prediction is important to activate the assistance system correctly. Our objectives are to propose a trajectory prediction method for ADAS for safe intersection turnings and to evaluate the effectiveness of the proposed prediction method. Our proposed curve generation method is capable of generating a smooth curve without discontinuities in the curvature. By incorporating the curve generation method into the vehicle trajectory prediction, the proposed method could simulate the actual driving path of human drivers at a low computational cost. The curve would be required to define positions, angles, and curvatures at its initial and terminal points. Driving experiments conducted at real city traffic intersections proved that the proposed method could predict the trajectory with a high degree of accuracy for various shapes and sizes of the intersections. This paper also describes a method to determine the terminal conditions of the curve generation method from intersection features. We set a hypothesis where the conditions can be defined individually from intersection geometry. From the hypothesis, a formula to determine the parameter was derived empirically from the driving experiments. Public road driving experiments indicated that the parameters for the trajectory prediction could be appropriately estimated by the obtained empirical formula.

scholarly journals Advanced Driver Assistant Systems Focused on Pedestrians’ Safety: A User Experience Approach

2021 ◽  
Vol 13 (8) ◽  
pp. 4264
Author(s):  
Matúš Šucha ◽  
Ralf Risser ◽  
Kristýna Honzíčková
Keyword(s):  
Autonomous Vehicles ◽  
Qualitative Data ◽  
Expert Interviews ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Assistant Systems ◽  
Vehicle Technology ◽  
Assistance Systems ◽  
Technical Solutions ◽  
Near Future

Globally, pedestrians represent 23% of all road deaths. Many solutions to protect pedestrians are proposed; in this paper, we focus on technical solutions of the ADAS–Advanced Driver Assistance Systems–type. Concerning the interaction between drivers and pedestrians, we want to have a closer look at two aspects: how to protect pedestrians with the help of vehicle technology, and how pedestrians–but also car drivers–perceive and accept such technology. The aim of the present study was to analyze and describe the experiences, needs, and preferences of pedestrians–and drivers–in connection with ADAS, or in other words, how ADAS should work in such a way that it would protect pedestrians and make walking more relaxed. Moreover, we interviewed experts in the field in order to check if, in the near future, the needs and preferences of pedestrians and drivers can be met by new generations of ADAS. A combination of different methods, specifically, an original questionnaire, on-the-spot interviewing, and expert interviews, was used to collect data. The qualitative data was analyzed using qualitative text analysis (clustering and categorization). The questionnaire for drivers was answered by a total of 70 respondents, while a total of 60 pedestrians agreed to complete questionnaires concerning pedestrian safety. Expert interviews (five interviews) were conducted by means of personal interviews, approximately one hour in duration. We conclude that systems to protect pedestrians–to avoid collisions of cars with pedestrians–are considered useful by all groups, though with somewhat different implications. With respect to the features of such systems, the considerations are very heterogeneous, and experimentation is needed in order to develop optimal systems, but a decisive argument put forward by some of the experts is that autonomous vehicles will have to be programmed extremely defensively. Given this argument, we conclude that we will need more discussion concerning typical interaction situations in order to find solutions that allow traffic to work both smoothly and safely.

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