Project Partners

“Developing automated driving and intermodal mobility concepts for the complex and dynamic traffic situation in the city is an extremely challenging task. Not only from a technological point of view. The human factor in all its facets must also be considered. In addition, cities differ in their transport philosophies, sometimes strikingly so. With STADT:up, we are tackling these challenges in a network of strong partners from the automotive and supplier industry, supported by research institutes and universities, and are working together on a pre-competitive basis. Together, we will not only significantly advance the technologies required for automated driving compared to the current state of the art, but also provide concepts for sustainable, intermodal urban mobility."

 

Dr Lutz Bürkle, Robert Bosch GmbH, STADT:up Project Coordinator

Aptiv Services Deutschland GmbH
 

In the field of RADAR perception, Aptiv is contributing its expertise as a long-standing supplier in this area. A second focus in the project is the prediction of road users. Issues such as the integration of traffic rules into the prediction models are being developed. The use of these prediction models should contribute to the improvement of behaviour or trajectory planning. Scene understanding is supported by the development of signatures and sensor-based maps to describe the traffic scene. Aptiv is also involved in the modelling of vehicle passengers; the state of the passengers must be monitored in order to answer questions about the ability of the driver to take over, but also for use in autonomous taxi services.more information

AVL Deutschland GmbH
 

Bundesanstalt für Straßenwesen
 

In STADT:up, the Federal Highway Research Institute (BASt) is developing and evaluating an adaptive HMI for various SAE levels for continuous vehicle automation and teleoperation and is researching the training of mode awareness and intended use. BASt is also contributing to the project with a demonstrator setup for continuous automated driving across different SAE levels and traffic scenarios.more information

CARIAD SE
 

In the STADT:up project, CARIAD SE is pursuing the prototypical implementation of an end-to-end automated journey in inner-city traffic. To this end, functional modules will be used along the entire chain of effects, with CARIAD focusing on situation analysis and behaviour generation. New algorithms are being developed and prototypically implemented using both conventional and AI methods. Another important factor is the human factors aspects, which, as a concept and in a prototype implementation, highlight the information required to understand the situation and the next actions.more information

Continental Automotive Technologies GmbH
 

The realisation of an empathic assistance for automated driving in the city is the main focus of Continental Automotive Technologies GmbH's work. The assistance concept is intended to have a regulatory effect on the affective states of users – such as fear, annoyance or boredom – and make an important contribution to ensuring that users trust the automation system like a "real" driver and that situations of discomfort are avoided. The empathic assistant is evaluated in various simulation scenarios with regard to usefulness, comfort, system trust and affective regulation.more information

Continental Autonomous Mobility Germany GmbH
 

The aim of Continental Autonomous Mobility GmbH is to demonstrate end-to-end automated driving in challenging urban scenarios in two prototypes. The focus here is on improving perception algorithms based on raw data, downstream fusion and data association using machine learning and coupling these with conventional approaches. This recombination using multimodal sensor technology is intended to improve perception and context detection and thus also the prediction of scenes in the course of traffic.more information

DeepScenario GmbH
 

In STADT:up, DeepScenario focusses on the development of novel 3D image processing algorithms for the extraction of traffic data from stationary, monocular cameras. A key objective here is to increase the detection and tracking accuracy of existing approaches with the help of machine learning methods. Both synthetic and real traffic images are used as the basis for the development and evaluation of the data-driven image processing algorithms.more information

DENSO ADAS Engineering Services GmbH
 

DENSO is focussing on the robustification of camera-based perception. Improving sensitivity to interference, caused by environmental conditions and infrastructure, are issues that need to be resolved. DENSO is also focussing on robustification against decalibration (accident, ageing) of the sensors used, especially from the point of view of machine learning. In addition to increasing and maintaining performance, the development tools are also optimised in a problem- and solution-oriented manner.more information

Deutsches Zentrum für Luft- und Raumfahrt e.V.
 

The focus of the DLR Institute of Transportation Systems starts with the exchange of requirements and use cases between local authorities and technology companies and moves on to the design and development of a digital twin that maps user requirements and experiences and enables their evaluation. With the help of holistic HMI concepts, consistent interactions between users and surrounding road users are realised, and a display and interaction concept for the workplace of the technical supervisor (teleoperator) is developed and prototypically tested. Furthermore, the focus is on holistic research into human cooperative interaction behaviour – in simulation scenarios as well as in real road traffic.more information

Ergosign GmbH
 

Ergosign designs and evaluates interaction concepts for the comprehensible and efficient explanation of automation behaviour to increase the acceptance, trust, situational awareness and sense of security of vehicle occupants in complex inner-city traffic situations. These concepts are demonstrated in simulator and real vehicle studies. Ergosign is also developing an engineering UI that processes sensor and vehicle information in real time and thus provides system engineers with valuable information and functions in the development process.more information

gestigon GmbH
 

The aim of gestigon is to realise an interaction between humans and the environment model through gesture and gaze direction recognition. To this end, gestigon will utilise a time-of-flight-based system for gesture recognition and a VR system with integrated gaze direction recognition. Both systems already exist and will serve as a starting point for the development of a simulation environment consisting of a vehicle cockpit and driving simulation as part of the project. This simulator will be used to generate AI training data, conduct user studies and implement a demo for interacting with selected points of interest.more information

HELLA GmbH & Co. KGaA
 

As part of the funding project, HELLA is working on integrated xHMI solutions for the vehicle interior and exterior. Comprehensive concepts are to be developed and evaluated as part of a holistic view of the scenarios. The users of the systems are placed at the centre of consideration in terms of safety, acceptance and comfort. HELLA is also involved in user modelling concepts and contributes its expertise in the fields of sensor technology, light-based communication and vehicle integration.more information

Hochschule für angewandte Wissenschaften München
 

In the STADT:up project, HM Hochschule München University of Applied Sciences is working on the recording and modelling of appearance-based communication and interaction features as well as the derived, accurate intention estimation and behaviour prediction of road users. In terms of algorithms, the focus is on learning, scalable and data-driven processes. In particular, the modelling also focuses on vulnerable road users. The newly developed concepts are prototypically presented in the test vehicle using automated driving functions.more information

Mercedes-Benz AG
 

Mercedes-Benz AG sees it as a major challenge to (further) develop existing assistance systems (up to level 2) and future automated driving (from level 3) for the inner-city traffic and to make the range of functions, starting from the motorway situation, also available for private vehicles in urban areas with vulnerable road users, complex intersections and oncoming traffic. The aim is to significantly improve the entire chain of effects from multi-sensor perception and fusion to prediction and manoeuvre planning – the intelligent backbone of automated driving, so to say – with the help of AI methods and machine learning.
more information

Opel Automobile GmbH
 

Opel Automobile GmbH is participating at the STADT:up research project with a focus on environmental perception for automated driving. Artificial intelligence methods – particularly those based on deep neural networks – are applied and improved for challenging perception tasks. The research team targets dependable detection of static and dynamic road users and objects. Methods for fusion of different sensor modalities such as camera, LiDAR and radar as well as the time-consistent tracking of objects support the performance of the system. The developed architectures and algorithms are implemented in an Opel vehicle. The improved environmental perception will be evaluated for critical cases and scenarios. The results will be presented by our engineers, who are part of the Stellantis research network, together with the consortium partners at the joint dissemination event.more information

Robert Bosch GmbH
 

In STADT:up, Bosch is pursuing the goal of continuous automated driving in inner-city traffic and will implement this as a prototype in the test vehicle. To this end, Bosch is developing both user-centred interaction concepts for the cooperation between humans and automated vehicles and AI-based methods along the entire signal processing chain of automated driving, from environmental perception detection and sensor data fusion to behaviour prediction, understanding intentions and interaction between road users and behaviour planning.more information

Technische Universität Chemnitz
 

In STADT:up, the research and development focus of Chemnitz University of Technology is on the comfort experience in automated driving. In user studies in driving simulators and test vehicles, the emerging discomfort is predicted by sensor data for advanced occupant state detection. Based on this, driving style and information presentation in automated driving are adapted.more information

Technische Universität Darmstadt
 

In the "Human Factors" sub-project of the STADT:up project, TU Darmstadt is researching the interaction between humans and automated vehicles and the design of human-machine interfaces (HMIs). Concepts and HMI prototypes are being developed from a human-centred perspective to demonstrate fully automated driving in the city with a focus on "Shared control in automated vehicle guidance", "User-centred concepts of teleoperation" and "Cooperation in everyday traffic situations". In the sub-project "Perspectives of Urban Mobility", TU Darmstadt is researching sustainable transport concepts for automated mobility in the city. Of central importance here is the question of how mixed traffic consisting of pedestrians, cyclists, private or shared vehicles and public transport will develop in the future.more information

Technische Universität München
 

Chair of Ergonomics:
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Chair of Traffic Engineering and Control:
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Valeo Schalter und Sensoren GmbH
 

In the STADT:up project, Valeo is pursuing the goal of advancing automated driving in the city using driving levels 0-4. One focus of the work is on improved and more robust perception using AI and a resulting extended environment model. In cases where automated driving is not possible or fails, teleoperation is intended to help. The demonstration of these and other driving functions in a continuous automated journey is part of Valeo's work. This includes driving through a junction, a bottleneck and, as a special feature, the demonstration of remote monitoring and teleoperation of the test vehicle in special situations.more information

ZF Friedrichshafen AG
 

The focus of activities in the STADT:up project is in the area of human factors, in relation to "complex" and "natural" traffic situations in mixed traffic. To this, ZF is working on a concept of scalable information depth of xHMI for different traffic situations, including initial validation and implementation in a demonstrator.more information

3D Mapping Solutions GmbH
 

3D Mapping provides the preparation of high-precision map data in various formats for use in simulation and in the vehicle and provides suitable 3D models. In particular, the integration of HD map data and 3D models into the various simulation tools available on the market as a basis for the simulation is a highly complex and elaborate task that can be solved within the scope of the project with the involvement of the users in the project consortium.more information