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Preference center

Tom Alkim, Strategic Advisor Connected & Automated Mobility for the Dutch company MAPtm and recently inducted into the Intertraffic International Advisory Board, traveled to Atlanta for the ITS World Congress and ITFVHA.

CCAM on the Move: Global Insights from ITS World Congress Atlanta

La definición de la Comisión Europea sobre la Movilidad Conectada, Cooperativa y Autónoma es interesante:
En muchos aspectos, los vehículos de hoy ya son dispositivos conectados. Sin embargo, en un futuro cercano, también interactuarán directamente entre sí y con la infraestructura vial.

EL CAMINO ES LARGO... El Desarrollo, Implementación y Desafíos del CCAM

“In many respects today's vehicles are already connected devices. However, in the very near future they will also interact directly with each other and with the road infrastructure. This interaction is the domain of Cooperative Intelligent Transport Systems (C-ITS), which will allow road users and traffic managers to share information and use it to coordinate their actions. This cooperative element – enabled by digital connectivity between vehicles and between vehicles and transport infrastructure – is expected to significantly improve road safety, traffic efficiency and comfort of driving, by helping the driver to take the right decisions and adapt to the traffic situation.”

THE ROAD IS LONG… The Development, Deployment and Challenges of CCAM

El año está pasando volando, y ahora solo faltan tres meses para que Intertraffic Américas 2025 abra sus puertas. El evento de tecnología vial más importante del continente se llevará a cabo del 17 al 19 de junio en el Centro Citibanamex de la Ciudad de México. Contará con un programa de conferencias fascinante y un piso de exhibición completamente lleno, que incluirá una emocionante zona de demostraciones.

Intertraffic Americas 2025: Movilidad inteligente, segura y sostenible para todos

The V2X sector, despite 25+ years of progress, grapples with privacy issues. Privacy concerns stem from historical mistrust, fear of surveillance, and varied attitudes toward data disclosure. Balancing benefits of V2X with individual privacy is challenging. Effective communication and education are crucial to address concerns. While government responsibility is debated, industry players and consumers must find solutions. Privacy concerns vary globally, with the U.S. likely expressing higher levels. Road authorities preparing for autonomy should focus on foundational elements, data security, and effective communication to ease privacy worries.

Intertraffic Americas 2025: SMART, SAFE, AND SUSTAINABLE MOBILITY FOR ALL

Luxemburgo reclama ser la región más progresista de Europa en términos de movilidad, al incorporar vehículos autónomos, y movilidad conectada y automatizada (CCAM), junto con una infraestructura ciclista mejorada y transporte público gratuito, además de una política que nunca desincentive el uso del automóvil. ¿Es realmente posible tenerlo todo?

¿Cómo crear un sistema de movilidad inteligente y multimodal?

Luxembourg is laying claim to being the most progressive region in Europe when it comes to mobility, by incorporating autonomous vehicles and CCAM with enhanced cycling infrastructure and free public transit, alongside a policy of never disincentivizing car use. Is it really possible to have it all?

How to create a smart, multimodal mobility system

V2X: Why is Privacy still such a Burning Issue?

Machine learning and artificial intelligence (ML/AI) are crucial in training autonomous vehicles (AVs) to understand and predict human driver behavior, mitigating errors. Univ.-Prof. Dr.-Ing. Lutz Eckstein from RWTH Aachen University discusses using deep neural networks, drone data, and roadside units to enhance AV perception. He emphasizes that AVs, with their constant vigilance and lack of distractions, have advantages over human drivers. European regulatory frameworks, requiring proof of safe AV behavior, contribute to safer deployment. Researchers aim to imbue AVs with a "seventh sense," mimicking experienced human drivers' decision-making capabilities to enhance safety.

How Machine Learning is Teaching Autonomous Vehicles To Factor in Driver Error

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