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Over the last 20 years, and particularly the last 10, China has been at the forefront of what has been nothing short of a mobility revolution. Driven by rapid urbanization, unprecedented scale and groundbreaking technological advancements, the world's second-most populous country's mobility developments have had and will continue to have far-reaching implications that extend beyond its land borders. Understanding these developments and their significance is crucial for policymakers, businesses and individuals worldwide.

China's mobility revolution (and why everyone else should take notice!)

In the third of our series of articles in which we talk to Intertraffic Amsterdam 2024 Summit Speakers, we discuss the importance of data to connected vehicles (and autonomous pods) with Contra Costa Transportation Authority’s (CCTA) Tim Haile and Randy Iwasaki, former CCTA director and now representing the Advanced Mobility Analytics Group

Expert Insights: Randy Iwasaki and Tim Haile delve into data driven solutions in connected and autonomous driving

Tomas Ohlson, Founding Engineer & SVP Technology of Einride, the Swedish electric and autonomous truck pioneers, answers Intertraffic’s probing questions

Electric & Autonomous Vehicles: Driving the Transition

Intertraffic explores the impact ChatGPT has on the development of smart mobility including utilisations for autonomous driving, road safety, and city planning.

Smart Mobility with Chat GPT-4: Transport just got even more intelligent

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.

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

It’s a debate that has been raging for the best part of two decades – when will autonomous vehicles be a commonplace sight on our roads? In the year 2021 we asked that question to several experts in the field. Find the three most important developments summed up in this article.

Latest Developments Cooperative Connected and Automated Mobility

The typical Silicon Valley start-up approach to innovation is to move fast and break things, as the famous maxim from Facebook founder Mark Zuckerberg goes. But in the highly complex world of autonomous vehicles and other safety critical applications breaking a few things along the way to our end goal isn’t something that we can shrug off so easily.

Unlocking the Future of Autonomous Mobility

Uber reveals new ecomobility measures

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