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SWARMS: Swarm Intelligence for Autonomous Cars

Subject Area Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Term from 2015 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 273356841
 
In this project we want to advance the state of the art towards achieving peaceful coexistence between autonomous and non-autonomous vehicles. Our vision for the future is that autonomous and non-autonomous vehicles will recognize the implicit or explicit intentions of traffic participants, will communicate and will cooperate. During a transition phase comprising several decades, autonomous vehicles must adapt to the traffic produced by human drivers. We propose to recognize the intentions of other drivers using the trajectories, speeds, and state of their vehicles, matched to the map of the city using graph fusion. We distinguish between "implicit" and "explicit" intentions. Explicit intentions can be communicated using a V2V and V2X communication unit. Implicit intentions must be extracted from the relationship between the current vehicle behavior, the constraints of traffic, and the map of the city. While autonomous vehicles can communicate their intended trajectory to surrounding autonomous vehicles, so that they adapt their behavior, it is not obvious how to present this information to human drivers. We propose to test two kinds of HMI: in one form of interaction the information is just passed in a graphic or haptic manner to the driver, in the second form of interaction an autonomous car, or a central computer, can set constraints to the human driver. We propose to implement swarm behavior for autonomous vehicles. Our extensive tests in three countries (in Berlin, Germany, in San Antonio, USA, and in Mexico City) have shown that while human drivers adapt immediately to changes in the environment, or in the map of the city, even in the absence of traffic markings (for example for lanes), this is still extremely difficult for robotic cars. Thus, we want to extend our navigation software so that in the absence of lane markings, or even in the absence of a map, an autonomous car can become part of a "driving swarm" and can steer with the flow. Other than safer autonomous navigation, immediate further applications of the technology to be developed consist of: the creation of city maps on-the-fly (that is, with one single manual drive), autonomous path-planning without marked lanes and in unstructured environments, as well as driving in car pools.
DFG Programme Priority Programmes
 
 

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