Automotive Architecture Topologies: Analysis for Safety-Critical Autonomous Vehicle Applications

Frigerio, Alessandro; Vermeulen, Bart; Goossens, Kees

doi:10.1109/access.2021.3074813

Cited by 21 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are approaches in which the ZCUs only transmit the data to a central processing unit. It is also possible to process zone-related functions directly on the ZCU in order to relieve the central processing unit and the communication volume [8,20]. An approach towards the ZCU are generic ECUs as proposed by Tomar [21].…”

Section: Power Supply Inmentioning

confidence: 99%

“…The zonal architecture solves this problem for the HV cables but only under certain conditions. Most concepts currently show the use of only one HV battery [7,8,20,45,46]. However, since the driver is no longer available as a fallback level due to autonomous driving functions, at least one energy storage device must be available in the event of a traction battery failure, providing the energy for driving an emergency trajectory.…”

Section: Research Gap and Contributionsmentioning

confidence: 99%

See 1 more Smart Citation

Design of Zonal E/E Architectures in Vehicles Using a Coupled Approach of k-Means Clustering and Dijkstra’s Algorithm

Maier,

Reuss

2023

Energies

View full text Add to dashboard Cite

Electromobility and autonomous driving has started a transformation in the automotive industry, resulting in new requirements for vehicle systems. Due to its functions, the electrical/electronic (E/E) architecture is one of the essential systems. Zonal E/E architecture is a promising approach to tackle this issue. The research presented in this paper describes a methodology for determining the optimal number of zones, the position of the zone control units (ZCU), and the assignment of electric components to these zones and ZCUs. Therefore, the design of the power supply and the wiring harness is essential. This approach aims to identify the most suitable system architecture for a given vehicle geometry and a set of electric components. For this purpose, the assignment of electric components is accomplished by k-means clustering, and Dijkstra’s algorithm is used to optimize the cable routing. As ZCUs will be the hubs for the in-vehicle data and information transport in zonal architectures, their position and their number are crucial for the architecture and wiring harness development. Simulations show a suitable zonal architecture reduces wiring harness length as well as weight and brings functional benefits. However, the number of zones must be chosen with care, as there may also be functional limitations.

show abstract

Section: Power Supply Inmentioning

confidence: 99%

Section: Research Gap and Contributionsmentioning

confidence: 99%

Design of Zonal E/E Architectures in Vehicles Using a Coupled Approach of k-Means Clustering and Dijkstra’s Algorithm

Maier,

Reuss

2023

Energies

View full text Add to dashboard Cite

show abstract

“…Hot-patching [22,23] provides seamless updates on tasks at runtime, but the task should stay in a single system that is not a direct solution for scheduling overheads. Redundancy [24,25], multiprocessing [18][19][20], and heterogeneous global scheduling [26] comprise hardware configurations and are mainly targeted to perform a singular concrete system, which may cause a single point of failure (SPOF) in system failure. Mobile agent- [27][28][29][30] and communication-based [31,32] works are helpful in the scope of distributed systems, but the objective is not task preservation.…”

Section: Related Workmentioning

confidence: 99%

Task Migration and Scheduler for Mixed-Criticality Systems

Baik

Lee

Kang

2022

Sensors

View full text Add to dashboard Cite

The interference between software components is increasing in safety-critical domains, such as autonomous driving. Low-criticality (LC) tasks, such as vehicle communication, may control high-criticality (HC) tasks, such as acceleration. In such cases, the LC task should also be considered as an HC task because the HC tasks relies on the LC task. However, the difficulty in guaranteeing these LC tasks is the catastrophic cost of computing resources, the electronic control unit in the domain of vehicles, required for every task. In this paper, we theoretically and practically provide safety-guaranteed and inexpensive scheduling for LC tasks by borrowing the computational power of neighbored systems in distributed systems, obviating the need for additional hardware components. As a result, our approach extended the schedulability of LC tasks without violating the HC tasks. Based on the deadline test, the compatibility of our approach with the task-level MC scheduler was higher than that of the system-level MC scheduler, such that the task-level had all dropped LC tasks recovered while the system-level only had 25.5% recovery. Conversely, from the worst-case measurement of violated HC tasks, the HC tasks were violated by the task-level MC scheduler more often than by the system-level MC scheduler, with 70.3% and 15.4% average response time overhead, respectively. In conclusion, under the condition that the HC task ratio has lower than 47% of the overall task systems at 80% of total utilization, the task-level approach with task migration has extensively higher sustainability on LC tasks.

show abstract

“…The automotive electrical/electronic (E/E) architecture is also changing as the number of sensors increases. The conventional automotive E/E architecture follows a decentralized design, consisting of numerous electronic control units (ECUs) distributed throughout the vehicle [7]. Each ECU is responsible for processing data from different sensors, and in cases where additional sensors are required, they must be connected to specific ECUs, even if the distance between the sensor and the ECU is considerable.…”

Section: Introductionmentioning

confidence: 99%