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Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility

Title data

Vermesan, Ovidiu ; John, Reiner ; Pype, Patrick ; Daalderop, Gerardo ; Kriegel, Kai ; Mitic, Gerhard ; Lorentz, Vincent ; Bahr, Roy ; Sand, Hans Erik ; Bockrath, Steffen ; Waldhör, Stefan:
Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility.
In: Frontiers in Future Transportation. Vol. 2 (26 August 2021) . - No. 688482.
ISSN 2673-5210
DOI: https://doi.org/10.3389/ffutr.2021.688482

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
ArchitectECA2030: Trustable architectures with acceptable residual risk for the electric, connected and automated cars877539
AI4DI: Artificial Intelligence for Digitizing Industry826060
SECREDAS: Product Security for Cross Domain Reliable Dependable Automated Systems783119
AI4CSM: Automotive Intelligence for/at Connected Shared Mobility101007326

Project financing: Andere
This work was supported by the European Commission within the European Union’s Horizon 2020 research and innovation programme funding, ECSEL Joint Undertaking project ArchitectECA2030 under Grant Agreement No. 877539, ECSEL Joint Undertaking project AI4DI under Grant Agreement No. 826060, ECSEL Joint Undertaking project SECREDAS under Grant Agreement No 783119 and ECSEL Joint Undertaking project AI4CSM under Grant Agreement No. 101007326.

Abstract in another language

The automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles. This brings cutting-edge computing paradigms with embedded cognitive capabilities into vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Digital technologies are a significant enabler in achieving the sustainability goals of the green transformation of the mobility and transportation sectors. Innovation occurs predominantly in ECAS vehicles’ architecture, operations, intelligent functions, and automotive digital infrastructure. The traditional ownership model is moving toward multimodal and shared mobility services. The ECAS vehicle’s technology allows for the development of virtual automotive functions that run on shared hardware platforms with data unlocking value, and for introducing new, shared computing-based automotive features. Facilitating vehicle automation, vehicle electrification, vehicle-to-everything (V2X) communication is accomplished by the convergence of artificial intelligence (AI), cellular/wireless connectivity, edge computing, the Internet of things (IoT), the Internet of intelligent things (IoIT), digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs). Vehicles become more intelligent, connected, functioning as edge micro servers on wheels, powered by sensors/actuators, hardware (HW), software (SW) and smart virtual functions that are integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information, either directly or indirectly, with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routes, infrastructure information, traffic lights, tolls, parking (micropayments), and finding emergent/intelligent solutions. The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles to support the acceleration of deployment in various mobility scenarios. ECAS vehicles, systems, sub-systems, and components are subjected to stringent regulatory frameworks, which set rigorous requirements for autonomous vehicles. An in-depth assessment of existing standards, regulations, and laws, including a thorough gap analysis, is required. Global guidelines must be provided on how to fulfill the requirements. ECAS vehicle technology trustworthiness, including AI-based HW/SW and algorithms, is necessary for developing ECAS systems across the entire automotive ecosystem. The safety and transparency of AI-based technology and the explainability of the purpose, use, benefits, and limitations of AI systems are critical for fulfilling trustworthiness requirements. The article presents ECAS vehicles’ evolution toward domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence in the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: artificial intelligence; electric connected autonomous and shared vehicles; internet of vehicles; edge computing; automotive architectures; swarm intelligence; vehicle-to-everything communication; green mobility
Institutions of the University: Research Institutions > Research Centres > Bayerisches Zentrum für Batterietechnik - BayBatt
Result of work at the UBT: No
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 03 Jun 2022 06:04
Last Modified: 03 Jun 2022 06:32
URI: https://eref.uni-bayreuth.de/id/eprint/69838