Funded by: Bundesministerium für Arbeit und Soziales (BMAS) im Rahmen der Initiative Neue Qualität der Arbeit (INQA)
Duration: 01/2021 - 12/2023
Contact: Prof. Dr. Vera Hagemann (Profil)
Abstract: The project "Artificial Intelligence for Healthy Work in Driving Professions: Workload and Safety in Traffic and Transportation (KARAT)" implements an employee-oriented artificial intelligence application to support driving professions in Germany. By using not only individual data, physiological reactions and driving data, but also publicly available data (e.g. weather data, major events, traffic situations), an analysis on workload based on machine learning is being developed. This application enables the prediction of the individual optimal driving and shift scheduling from a health and work perspective and suggests measures for stress reduction as well as optimal work, assignment and route planning. For companies, this offers the possibility of reducing the specific workload and the high level of sickness and absenteeism in driving occupations by means of a standardized procedure with little effort. At the same time, in the group of driving professions with a total of about 1.5 million employees in Germany, a specific benefit is demonstrated through the use of AI applications, which provides an example and motivation for other fields of application of AI to support healthy work beyond the specific areas of application. The project consortium consists of the experienced research partners FOM Hochschule Essen (coordination), University of Bremen, University of Duisburg-Essen and University of Hohenheim as well as the practice partners Duisport Group (Duisburg), the SME transport company Sherwood (Cologne) and the freight forwarding association VSL NRW (Düsseldorf).
This means that larger and smaller organizations with significant numbers of employees in driving professions are represented (total number of employees through more than 500 VSL member companies about 100,000). In addition, eleven associated project partners support the research work in the direction of a far-reaching transfer effect, for example, in the area of driving activities of local public transport. Challenges posed by the digital transformation are positively addressed by the KARAT project, as the density of digital systems is increasing for driving professions: digital systems are increasingly being used for navigation, toll collection, order control or customer data collection. This results in a networking potential through individualized AI systems for stress analysis and reduction for employees in driving professions. More.