Related papers: Zonal Architecture Development with evolution of A…
Centralization is considered as a key enabler to master the CPU-intensive features of the modern car. The development and architecture change towards the next generation car is influenced by ADAS, connectivity, infotainment and the…
Current automotive E/E architectures are subject to significant transformations: Computing-power-intensive advanced driver-assistance systems, bandwidth-hungry infotainment systems, the connection of the vehicle with the internet and the…
The transition toward Software-Defined Vehicles (SDVs) represents a major paradigm shift in vehicle design, transforming traditional hardware-centric systems into software-centric platforms capable of dynamic adaptation and continuous…
Multiple studies have illustrated the potential for dramatic societal, environmental and economic benefits from significant penetration of autonomous driving. However, all the current approaches to autonomous driving require the automotive…
As in-vehicle communication becomes more complex, the automotive community is exploring various architectural options such as centralized and zonal architectures for their numerous benefits. Zonal architecture reduces the wiring cost by…
The safety of an automated vehicle hinges crucially upon the accuracy of perception and decision-making latency. Under these stringent requirements, future automated cars are usually equipped with multi-modal sensors such as cameras and…
The advent of autonomous vehicles has heralded a transformative era in transportation, reshaping the landscape of mobility through cutting-edge technologies. Central to this evolution is the integration of Artificial Intelligence (AI) and…
The last decade witnessed increasingly rapid progress in self-driving vehicle technology, mainly backed up by advances in the area of deep learning and artificial intelligence. The objective of this paper is to survey the current…
The growing need for intelligent, adaptive, and energy-efficient autonomous systems across fields such as robotics, mobile agents (e.g., UAVs), and self-driving vehicles is driving interest in neuromorphic computing. By drawing inspiration…
Artificial intelligence (AI) technologies have dramatically advanced in recent years, resulting in revolutionary changes in people's lives. Empowered by edge computing, AI workloads are migrating from centralized cloud architectures to…
This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research directions for generative artificial intelligence and foundation…
The recent advent of connected and automated vehicles (CAVs) is expected to transform the transportation system. CAV technologies are being developed rapidly and they are foreseen to penetrate the market at a rapid pace. On the other hand,…
Multi-sensor fusion plays a critical role in enhancing perception for autonomous driving, overcoming individual sensor limitations, and enabling comprehensive environmental understanding. This paper first formalizes multi-sensor fusion…
In the burgeoning field of intelligent transportation systems, the integration of Generative Artificial Intelligence (AI) into vehicular networks presents a transformative potential for the automotive industry. This paper explores the…
Mobility is the backbone of urban life and a vital economic factor in the development of the world. Rapid urbanization and the growth of mega-cities is bringing dramatic changes in the capabilities of vehicles. Innovative solutions like…
We provide a summary over architectural approaches that can be used to construct dependable learning-enabled autonomous systems, with a focus on automated driving. We consider three technology pillars for architecting dependable autonomy,…
The remarkable progress in Artificial Intelligence (AI) is foundation-ally linked to a concurrent revolution in computer architecture. As AI models, particularly Deep Neural Networks (DNNs), have grown in complexity, their massive…
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of…
This survey explores the adaptation of visual transformer models in Autonomous Driving, a transition inspired by their success in Natural Language Processing. Surpassing traditional Recurrent Neural Networks in tasks like sequential image…
This paper investigates a range of cutting-edge technologies and architectural innovations aimed at simplifying network operations, reducing operational expenditure (OpEx), and enabling the deployment of new service models. The focus is on…