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Hesse: Artificial Intelligence Shapes the Mobility of Tomorrow

(dpa/lhe/fn) More precise traffic forecasts, more efficient logistics processes, and better traffic management: Artificial intelligence in the field of mobility holds great potential but also poses challenges. 

A small camera between a warning sign and a traffic light captures the traffic situation on Rheinstraße. In the science city, additional cameras are mounted on many traffic light systems, which capture the traffic situation and evaluate it using AI. The goal: more accurate traffic forecasts, better traffic management, more safety. (Photo: Andreas Arnold/dpa)
A small camera between a warning sign and a traffic light captures the traffic situation on Rheinstraße. In the science city, additional cameras are mounted on many traffic light systems, which capture the traffic situation and evaluate it using AI. The goal: more accurate traffic forecasts, better traffic management, more safety. (Photo: Andreas Arnold/dpa)
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von Franziska Neuner

The mobility of the future relies on Artificial Intelligence. For Hesse, the topic of AI and mobility is a particularly important field, according to the Hessian Ministry of Digital Affairs.

"As a central federal state with nationally and internationally significant transport infrastructure, Hesse's Digital Minister has already anchored the topic of AI and mobility as one of three innovation fields in the Hessian AI Future Agenda published in 2022," a spokesperson explained. 

AI Plays Diverse Role in Mobility

"Artificial intelligence is already playing an important role in various areas of mobility," he explained.

Companies, research institutions, as well as cities and municipalities in Hesse, are working on a multitude of pioneering projects on how AI can improve mobility. 

One example is the use of a so-called traffic light phase assistant in Darmstadt. There, road traffic is controlled in real-time and depending on traffic volume.

"For this purpose, a connection of all 182 traffic light systems with the fiber optic network and an interface was created." 200 cameras transmit anonymized images of traffic volume to the traffic computer's database. "An AI evaluates this data to optimize the traffic light control." 

High Demands in AI Development

General challenges in AI development include high demands on data, computing capacities, skilled workers, and financing, the spokesperson explained.

"The EU AI regulation establishes a new regulatory framework for AI development, which developers must familiarize themselves with. New standards for AI product safety must be followed." Some tasks in the mobility sector are technically highly demanding. "Autonomous driving is the best-known example here, with corporations investing billions over the years to bring the control systems closer to roadworthiness."

Translated automatically from German.
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