Research Cooperative Systems
The department is pioneering new autonomous mobility solutions by researching, designing, and demonstrating connection, automation, cooperation, and coordination for vehicles, system networks, and us humans.
KoKoVI – Transport as a co-operative and networked system
In order to meet society's future mobility needs and at the same time make road traffic safer, more efficient and more environmentally friendly, the German Aerospace Center's (DLR) Transport programme is working on technologies for networking individual road users in future mobility systems. In this way, the available road network can be optimally utilised. The KoKoVI project therefore sees traffic as a networked system in which the potential of automation and digitalisation can be exploited. Eight DLR institutes are jointly researching the networking and cooperation of vehicles, cyclists, pedestrians and traffic infrastructure systems such as traffic lights and sensors. The active integration of infrastructure components into the transport system is a central aspect of the project.
As a research result of the KoKoVI project, the components required for the planned use cases 'Virtual Stop' and 'Remote Operation' will be developed and demonstrated in urban traffic in Braunschweig. The possibilities of the Test Bed Lower Saxony and the Application Platform for Intelligent Mobility (AIM) for simulation-based development as well as real traffic detection, traffic control and networking will also be utilised for this purpose.
Virtual stop
New technological innovations and needs-based mobility concepts are required in order to adequately protect the climate and at the same time enable future mobility to an appropriate extent. It is important to optimise the use of available resources and, for example, to share vehicles as part of ride sharing. Automated driving can support the establishment of needs-based mobility services in rural and urban areas by developing automated shuttle services with virtual stops. Users can use an app on their smartphone to have the automated shuttle stop at any point along the route to get on or off. This avoids walking to regular stops and reduces long waiting times thanks to the real-time information in the app. Today's mobility service providers already offer shuttle services with flexible stops with manually driven vehicles in larger cities.
Users are guided to the digital stop via app.
However, the use of autonomous vehicles brings with it a number of new challenges, such as how the automated vehicle approaches and stops at the virtual bus stop while simultaneously taking other road users such as cyclists and moving and stationary traffic into account. In this use case, the scientists are therefore testing the entire process, from ordering the shuttle to arriving at a virtual stop and departing. The starting point is the ordering of a shuttle by the user via an app. Both the users and the shuttle then travel to the virtual stop. Various processes run in the background. For example, distribution software determines the location of the virtual stop and calculates the route for the vehicle. At the same time, the app also guides users there using augmented reality visualisations. Traffic lights that need to be crossed dynamically adapt their controls to the user's route and also block off areas of the carriageway so that the automated vehicle can stop safely. The shuttle then enters and leaves the vehicle.
Remote Operation
Research and developments in automated driving have made great strides in recent years and the first automated vehicles are driving in real traffic under controlled conditions (e.g. Waymo (USA), HEAT (Hamburg), First Mover (Berlin)). However, if unforeseen situations arise, such as a complicated roadworks site, with which the automated driving function is currently still overwhelmed, the current status at Waymo, for example, provides for technical supervision to be called in. This is also the current understanding in research. However, if automated shuttle services are extended to larger fleets and more extensive areas in the future, this solution strategy will no longer be manageable. Efficient solutions must therefore be developed to detect potentially problematic situations at an early stage and then solve and implement them efficiently. There are currently no implemented solutions for dealing with complicated situations in which the vehicle stops and does not continue its journey. Possible solutions currently range from re-routing and a short-term extension of the operating range of the automated driving functions using additional information from the infrastructure to the integration of the remote operator as an external technical supervisor that is networked with the vehicle and transmits an alternative route.
The remote operation use case therefore addresses unforeseen situations in which the automated driving function reaches its operating limits. The scientists are testing the verification of compliance with the operating limits of the automated driving functions and the execution of a remote operation by a technical supervisor as a possible solution option. For this purpose, the automated vehicle requests the remote operation and the remote operator initiates a corresponding solution.
The remote operator supports the automated vehicle outside the operational design domain.
Project title:
KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz
Duration:
01/2022 to 12/2024
Project volume:
€ 16.2 million full costs
Project coordinator:
DLR Institute of Transportation Systems
DLR institutes involved:
Flight Experiments
Institute of Flight Systems
Institute of Communications and Navigation
The Remote Sensing Technology Institute
Institute of Optical Sensor Systems
Institute of Systems Engineering for Future Mobility
Institute of Transport Research
Related projects:
Contact
Dr. Tobias Hesse
Head of Department
German Aerospace Center (DLR)
Institute of Transportation Systems
Research Cooperative Systems
Rutherfordstr. 2, 12489 Berlin