Sectors

AI is a generic technology that is ultimately applicable in all sectors. For the development of knowledge and experience in the use of AI in the Netherlands, it is essential to focus on specific industries that are relevant to our country. These industries can achieve excellent results, and knowledge and experience are extended for application in other sectors.

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Emilia Silvas

Chair working group Mobility, Transport and Logistics

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Mobility, Transport and Logistics

Mobility, Transport and Logistics are prime drivers of the Dutch economy. The need to strengthen the Dutch competitive position and to provide solutions to social issues such as employment, traffic safety, sustainability, congestions, comfort and air quality, stimulate innovation in mobility developments.

Artificial Intelligence (AI) plays an increasing role within these developments, and it is only possible to tackle these societal challenges with a cooperative approach. The social damage caused exclusively by traffic jams amounts to some 3 billion euros annually while the damage caused by traffic accidents amounts to some 15 billion euros, not counting the damage to health and the costs caused by emissions. The costs of mobility for citizens and businesses, revolve around 136 billion euros annually. AI can actively contribute to a mobility transition towards improved accessibility, sustainability and accident reduction. AI provides a solid way of securing the international economic prospects of the Dutch mobility sector.

Working group

The complexity of these developments, the amount of data available, and computing power are increasing rapidly and require a unified and integrated approach, and AI can provide solutions. The Mobility, Transport and Logistics working group, therefore, focuses on the most critical opportunities and challenges in this sector. The working group aspires to identify and develop AI solutions and addresses these by connecting partners and working together on concrete actions.

The working group focuses on the following challenges:
– AI for sustainable mobility (e.g. smart electric charging, self-learning energy management)
– AI for accessibility and fluidity (e.g. cooperative mobility, partial mobility)
– AI for safe, shared and flexible mobility (e.g. smart autonomous vehicles, public transport)
– AI for efficient logistics (e.g. smart planning systems, predictive maintenance, self-organising logistics)

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