Industry-track: System-Level Logical Execution Time for Automotive Software Development

Gemlau, Kai-Björn; Hasseln, Hermann von; Ernst, Rolf

doi:10.1109/emsoft55006.2022.00017

2022 International Conference on Embedded Software (EMSOFT) 2022

DOI: 10.1109/emsoft55006.2022.00017

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Industry-track: System-Level Logical Execution Time for Automotive Software Development

Kai-Björn Gemlau

Hermann von Hasseln

Rolf Ernst

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2023

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Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization

Peeck,

Ernst

2023

ACM Trans. Embed. Comput. Syst.

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Higher levels of automated driving also require a more sophisticated environmental perception. Therefore, an increasing number of sensors transmit their data samples as frame bursts to other applications for further processing. As a vehicle has to react to its environment in time, such data is subject to safety-critical latency constraints. To keep up with the resulting data rates, there is an ongoing transition to a Time-Sensitive Networking (TSN)-based communication backbone. However, the use of TSN-related industry standards does not match the automotive requirements of large timely sensor data transmission, nor it offers benefits on time-critical transmissions of single control data packets. By using the full data rate of prioritized IEEE 802.1Q Ethernet, giving time guarantees on large data samples is possible, but with strongly degraded results due to data collision. Resolving such collisions with time-aware shaping comes with significant overhead. Hence, rather than optimizing the parameters of the existing protocol, we propose a system design that synchronizes the transmission times of sensor data samples. This limits network protocol complexity and hardware requirements by avoiding tight time synchronization and time-aware shaping. We demonstrate that individual sensor data samples are transmitted without significant interference, exclusively at full Ethernet data rate. We provide a synchronous event model together with a straightforward response time analysis for synchronous multi-frame sample transmissions. The results show that worst-case latencies of such sample communication, in contrast to non-synchronized approaches, are close to their theoretical minimum as well as to simulative results while keeping the overall network utilization high.

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Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization

Peeck,

Ernst

2023

ACM Trans. Embed. Comput. Syst.

View full text Add to dashboard Cite

show abstract

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Industry-track: System-Level Logical Execution Time for Automotive Software Development

Cited by 1 publication

References 5 publications

Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization

Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization

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