Real labs are used to gather experience with digital innovations under real conditions. Here, stakeholders from research, industry, municipalities and operators in urban and rural areas as well as for passenger and freight transportation can test new technologies and business models. 

As part of RABus, largely economical public transport operations with electrified and automated vehicles will be established in Mannheim and in Friedrichshafen. These electrified and automated vehicles will be able to “float along” in regular traffic by traveling at least 40 km/h in urban areas and at least 60 km/h outside urban areas.

Due to the positive results in the final phase of the RABus project, an extension of six months has been granted. The shuttles will continue to be used in regular service in Friedrichshafen until the end of June 2025 in order to gain additional insights into the future use of automated vehicles in local public transport - particularly with regard to urban-rural connections. The extended project duration will further advance technical development and create additional testing opportunities.

The consortium consists of the Research Institute of Automotive Engineering and Powertrain Sytems Stuttgart (FKFS), Stadtverkehr Friedrichshafen GmbH (SVF), Regionalverkehr Alb-Bodensee GmbH (RAB), Verkehrsbetrieb Rhein-Neckar-Verkehr GmbH (rnv), the Institute of Transportation (IfV) at the Karlruhe Institute of Technology (KIT) and ZF Friedrichshafen AG.

AIAMO is a project funded by the German Federal Ministry of Digital and Transport. Under the consortium leadership of ITS Germany e.V., 12 partners are working together to develop AI-based environmental and mobility management in order to make mobility more efficient, resource-saving, safe and demand-oriented.

www.aiamo.de

Mobility participants generate a wealth of data that often remains unused. In AIAMO, FKFS focuses on three main areas: data acquisition, digital twins and data augmentation. We develop model- and data-based software to refine the collected data and generate new data and insights from it. The work includes the development of a model each for tire, brake and car-following and the calibration of these models. As a first step, the current traffic and the resulting emissions will be measured in selected regions and used to parameterize the models. On this basis, the software should be able to be used for forecasts in order to quantify the influence of infrastructure changes and new types of connected driving functions (e.g. GLOSA).

Date augmentation deals with the generation of data when there is too little or no data available in terms of space and time. Using artificial intelligence and historical data, complex correlations can be learned and then generated at the push of a button. As with model-based forecasting mentioned above, we at FKFS focus on data-based forecasting. In addition, we are developing data augmentation methods to expand existing data sets and thus increase the data base.

SALSA is being developed by a consortium of 16 partners funded by the Federal Ministry of Economics and Climate Protection (BMWK).

In the near future, automated, autonomous and conventional vehicles will coexist in road traffic and share space with pedestrians, cyclists and other vehicle variants. However, lack of interaction, non-standardized communication and implausible driving behavior could lead to difficult situations and lower acceptance of these technologies.

SALSA aims to overcome these challenges by building the bridge from vehicles to other road users and from vehicle occupants to technology.

The focus of FKFS in SALSA is on driving behavior in mixed traffic. Our aim is to give passengers a high level of confidence in the vehicle systems to ensure a safe and confident driving experience. At the same time, driving behavior should be cooperative and predictable for other road users.

In the project, the highly immersive Stuttgart driving simulator will be used to study driving behavior. With its help we are going to conduct several studies with test subjects. As the Stuttgart driving simulator can realistically reproduce vehicle movements as well as the visual and acoustic vehicle environment, it is very well suited for investigating with test subjects in defined driving situations, how they react or what driving behavior they would like from a vehicle. Further advantages of the driving simulator are the ability to reproduce defined situations and the driving behavior of autonomous vehicles. In real road traffic, such investigations are not yet possible and would only be feasible at great expense.  

In SALSA, an initial study is being conducted at FKFS using an existing mock-up, a compact car, to investigate driving behavior during manual driving. For this purpose, especially critical traffic scenarios, in which a driver deliberately wants to override an assistance system, are going to be reproduced. The aim of this study is to identify characteristics by which a driver's intention can be recognized so that an assistance system does not unintentionally intervene in vehicle control.

Another project of FKFS within SALSA is the development of a new vehicle mockup, a minibus, for user-experience studies. This new mockup is designed in particular for topics relating to autonomous driving with SAE level 4. With this new UX mockup, FKFS is going to investigate how different occupants would like an autonomous vehicle to behave in different situations. In addition to driving behavior in everyday driving situations, another focus is on driving behavior in extreme situations, so-called minimum risk maneuvers, in which the autonomous vehicle has to perform an emergency stop. Even in these exceptional situations, occupants should always feel a high level of safety. In the Stuttgart driving simulator, it will be investigated how the driving behavior of an autonomous vehicle can contribute to the occupants feeling safe.

https://projekt-salsa.de/