Samsung is advancing solid-state battery technology with an innovative silver-carbon composite anode designed to address critical limitations of conventional lithium-ion batteries. The company's breakthrough involves a five-micrometer silver-carbon nanocomposite layer that suppresses dendrite formation—needle-like lithium structures that cause battery degradation and safety issues. This silver-stabilized architecture enables Samsung's "anode-less" design, achieving significantly enhanced performance metrics including 900 Wh/L energy density, 600-mile vehicle range, and nine-minute fast charging capabilities. With mass production targeted for 2027, this development signals a transformative shift in energy storage technology and introduces silver as a critical material in the evolving EV supply chain, positioning Samsung SDI as a leading innovator in next-generation battery solutions.

Digital twin technology has emerged as a critical infrastructure component in autonomous systems development, serving essential functions throughout design, validation, and operational phases. A digital twin represents a continuously synchronized virtual replica of a physical autonomous platform, encompassing sensors, actuators, control logic, and environmental interactions. Originally formalized by NASA in 2012, this technology spans multiple classification types, including geometric and kinematic twins for collision modeling and path planning, as well as physics-based twins for simulating complex behaviors and predictive maintenance. Digital twins directly support simulation, testing, safety certification frameworks, and real-time operational intelligence across ground, air, and industrial autonomous systems. By enabling continuous synchronization between virtual and physical platforms throughout the system lifecycle, digital twins facilitate enhanced validation procedures, reduce operational risks, and optimize maintenance strategies across diverse autonomous applications.

The International Energy Agency examines the symbiotic relationship between artificial intelligence and electric vehicle development. AI and advanced computing capabilities are disproportionately benefiting EVs, particularly in autonomous driving and integrated vehicle control systems. The stable, high-voltage power supply inherent to EV batteries creates an ideal environment for sensor and chip integration. While AI benefits extend beyond EVs to hybrid vehicles and general automotive design optimization, autonomous vehicle advancement fundamentally depends on machine learning algorithms and computational power. Modern autonomous vehicles employ diverse sensor arrays including cameras, radars, and lidars to create comprehensive environmental awareness, leveraging sophisticated AI techniques and neural networks that can navigate real-world driving complexity far beyond the limitations of earlier rule-based systems confined to test tracks.

Neuromorphic computing, which aims to replicate the brain's neuro-synaptic systems through hardware design, is emerging as a promising alternative to traditional computing architectures. Though still in early development, this technology is garnering significant interest from technology companies, scientists, and researchers across multiple sectors, including artificial intelligence, robotics, energy systems, and defence. The concept, originally introduced by Carver Mead at Caltech in the 1980s, involves creating electronic circuits that mimic the analogue behavior of neurons and synapses. However, considerable technical and commercial challenges must be resolved before determining the technology's practical applications and optimal deployment contexts.

Software-Defined Vehicles represent a fundamental paradigm shift in automotive design, transitioning from hardware-centric to software-centric platforms capable of dynamic adaptation and continuous evolution. This comprehensive survey examines SDV architectures, enabling technologies, and operational frameworks, tracing the evolution from distributed electronic control units to centralized computing platforms. The paper reviews critical technologies including service-oriented software architectures, middleware, artificial intelligence, and cloud-based infrastructures, while introducing a structured taxonomy organizing SDV technologies across functional hardware, electrical-electronic architectures, software frameworks, automation mechanisms, and distributed infrastructure. Additionally, the study explores the Software-Defined Internet of Vehicles paradigm, integrating software-defined networking with edge and fog computing to enable scalable vehicular communication, while addressing cybersecurity and interoperability challenges inherent to modern connected vehicles.

Stellantis has announced a strategic five-year collaboration with Microsoft to accelerate its digital transformation and AI-driven innovation. The partnership will focus on co-developing over 100 AI initiatives spanning sales, customer care, and operations across the automotive company's global ecosystem. Key initiatives include strengthening cybersecurity defenses with AI-powered analytics to protect vehicles and operations, and modernizing cloud infrastructure to reduce datacenter footprint by 60% by 2029. By combining Stellantis' automotive engineering expertise and multi-brand scale with Microsoft's cloud and AI capabilities, the collaboration aims to enhance customer experiences and drive operational agility across the organization.

Robotaxi networks are experiencing significant expansion into additional cities as commercial operations advance across the United States. This growth reflects increasing confidence in autonomous vehicle technology and its market viability. Companies are scaling their fleet operations to serve broader geographic regions, marking a pivotal moment in the transportation industry's evolution. As robotaxi services become more accessible, they promise to reshape urban mobility, reduce transportation costs, and address congestion challenges. The expansion demonstrates that autonomous vehicle technology has progressed from experimental phases into practical, revenue-generating operations that attract substantial investment and consumer interest.

Nissan is implementing significant restructuring across its European operations, cutting approximately 900 jobs—roughly ten percent of the region's workforce—as part of its broader Re:Nissan programme targeting 20,000 global job reductions. The majority of cuts affect white-collar and warehouse positions across the UK, France, and Spain, with production roles at the Sunderland plant protected despite consolidating from two manufacturing lines to one. The facility, operating at approximately fifty percent capacity, will maintain its status as an electric vehicle hub while streamlining operations to improve profitability. Additional measures include partial closure of Barcelona's parts warehouse and transition to importer-led distribution in Nordic markets. Spanish unions have strongly opposed the cuts, with negotiations expected to reduce Spain's allocation from the planned five hundred positions.

Nissan announced the closure of its production line at its Sunderland facility in the United Kingdom, resulting in the elimination of approximately 900 jobs across Europe. The Sunderland plant, which manufactures the Qashqai, Juke, and Leaf models, represents a significant shift in Nissan's European operations. This decision reflects broader challenges within the automotive industry, including manufacturing pressures and market dynamics. The closure is expected to have considerable implications for the UK automotive sector and Nissan's European workforce, marking a notable restructuring effort by the Japanese automaker.

Uber et la start-up Pony.ai lancent des essais de voitures autonomes destinées au marché européen. Ce partenariat vise à explorer le potentiel des robotaxis sur le continent, une étape stratégique pour l’essor de la mobilité sans conducteur en Europe.

La singularité technologique de Wayve réside dans sa pile logicielle « AV2.0 », qui s’appuie sur un modèle d’IA généralisée end-to-end. Contrairement aux approches classiques (architecture « sense-plan-act »), l’algorithme de conduite autonome traite directement les données brutes des capteurs (caméras, radars, voire LiDAR) pour piloter le véhicule. Concrètement, cela permet à un robotaxi équipé du système Wayve d’apprendre à circuler dans des environnements urbains variés sans recourir systématiquement à des cartes HD ou à une phase d’entraînement longue et locale.

L'usine, ouverte en 1937 par Ford, fut le haut lieu de Simca avant d'être reprise par PSA à la fin des années 1970, lorsqu'elle employait près de 27.000 salariés. Elle ne fermera pas ses portes pour autant. D'une part car elle accueillera toujours le « Green Campus » dédié à la R&D, aux fonctions support et aux activités de siège de Stellantis en France. D'autre part car le groupe va y localiser une palette d'activités pour « se consacrer aux différentes vies des véhicules », a-t-il indiqué. Pour cela, une enveloppe approchant les 100 millions d'euros sera mobilisée.

Un mois après la présentation du nouveau plan stratégique, c'est la soupe à la grimace pour les syndicats et les salariés de Renault. La direction du constructeur a annoncé vendredi à l'occasion d'un comité de groupe que 15 % à 20 % des postes de l'ingénierie seraient supprimés dans les deux ans à venir au niveau mondial.Selon des chiffres fournis par l'entreprise, Renault compte aujourd'hui près de 12.000 ingénieurs dans ses effectifs, dont la moitié hors de France. Le groupe compte également des centres d'ingénierie (des RTX dans le langage interne) en Roumanie, en Corée du Sud, en Inde, ou encore au Brésil et au Maroc.

Sale temps pour les ingénieurs dans l'automobile. Alors que Stellantis a prévenu vendredi de son intention de supprimer 650 postes dans le centre de développement d'Opel à Rüsselsheim (Allemagne), Renault va dans le même temps sortir la serpe dans ses équipes, avec une réduction de 15 % à 20 % dans les deux ans à venir, ce qui représente de 1.600 à 2.400 postes en moins dans le monde. Deux annonces concomitantes qui soulignent à quel point les ingénieries du secteur, en particulier en Europe, sont sous pression. La tendance ne date pas d'hier. Il y a trois ans, Ford Europe a engagé une réduction de 3.600 postes dans sa R&D en Allemagne et au Royaume-Uni. L'année suivante, l'équipementier Forvia a enclenché un plan de restructuration portant sur 10.000 emplois dans le monde d'ici à 2028, en ciblant plus particulièrement les fonctions support et recherche-développement. Le groupe Volkswagen, de son côté, prévoit de supprimer 50.000 emplois en Allemagne d'ici à 2030, et si la direction n'a pas pour l'instant fourni de chiffres plus précis, l'ingénierie ne sera à coup sûr pas épargnée.

Stellantis et Microsoft annoncent une collaboration stratégique de cinq ans visant à accélérer la transformation numérique du groupe automobile. Co-développement de plus de 100 initiatives d’intelligence artificielle, renforcement de la cybersécurité, modernisation de l’infrastructure cloud avec un objectif de réduction de 60 % de l’empreinte des data centers d’ici 2029 : l’accord couvre l’ensemble de la chaîne de valeur du groupe, de l’ingénierie à l’expérience client.

 Nissan has unveiled its ambitious future product strategy, as detailed by automotive journalist Alisa Priddle, on April 14, 2026. This plan highlights a transformative approach for the company, focusing on enhancing its global  vehicle lineup with a greater emphasis on hybrid technology, reducing the number of models offered, and integrating advanced artificial intelligence (AI) solutions into its operations. These strategic shifts are designed to position Nissan favorably amid the evolving landscape of the automotive sector.

Trajectory prediction is critical for autonomous vehicles, allowing them to anticipate the future movements of other agents on the road to ensure safety and smooth navigation. Traditional methods operate under the assumption of zero latency—an idealized scenario where predictions are made instantaneously without delay. However, in practical autonomous driving systems, latency is unavoidable due to the time required for data sensing, processing, and prediction calculations. The conventional oversight of this latency leads to predictions that are already outdated the moment they are generated, resulting in reduced accuracy and potential safety risks.

Le 15 avril 2026, Le Journal de l’Automobile a remis le titre de Personnalité Automobile de l’Année 2025 au directeur général de Valeo. Cette cérémonie a rassemblé les grands acteurs de la filière à la Maison de la Chimie, à Paris, pour saluer le rôle central de Christophe Périllat dans la transformation de l’industrie européenne et son engagement en faveur d’une politique industrielle ambitieuse.

A year ago, MOIA America and Uber unveiled an ambitious plan to launch a commercial robotaxi service — using autonomous versions of Volkswagen’s electric ID. Buzz minivan — in multiple U.S. cities over the next decade. Los Angeles is the first city on that list.Testing will start in the next few weeks with about 10 autonomous ID. Buzz vehicles in Los Angeles, according to the company. The production version of the driverless vehicle seats four people.

The catalyst is Waymo’s launch in Nashville, Tennessee, adding another city to a commercial robotaxi footprint that already includes San Francisco, Los Angeles, Phoenix, and Austin. For investors who have watched Alphabet pour billions into its self-driving bet for years, Nashville is more than a new pin on a map. It’s evidence that the commercial rollout is accelerating.