Complexity in cooperative traffic situations: Discrete-event modeling in automated vehicle guidance

• Applicants: Professorin Dr.-Ing. Barbara Deml; Professor Dr.-Ing. Michael Heizmann, since 9/2020
• Subject Area: Measurement Systems ; Human Factors, Ergonomics, Human-Machine Systems
• Term: from 2015 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 273388294

Research question. The project addresses the topics situation prediction and system ergonomics. In many traffic situations a breakdown will be observed when cooperation behavior is missing, despite of valid traffic rules. Such deadlock situations occur in urban X- and T-intersections or in coequal narrow passages regularly. Besides, our previous work has shown that a need of cooperation may also arise spontaneously when a traffic situation is solved differently than it is supposed to be. Furthermore, it is to be assumed that the complexity of a traffic situation has an important impact on the human cooperation behavior. Our objective is to gain a better understanding of how humans behave in such situations: Which environmental information is relevant for assessing a cooperative setting? How do we recognize the behavioral intention of cooperation partners? On the basis of these findings, an algorithm for situation prediction shall be derived, so that automatic vehicles are also able to overcome deadlock situations in cooperation with human drivers. Research methods and results. In order to achieve these goals, empirical studies are to be carried out: Besides a field experimental study and an observational traffic study within „Testfeld Autonomes Fahren Baden-Württemberg“ further experiments in a driving simulator are planned. As we assume that human cooperation behavior depends highly on traffic complexity, a suitable measure shall be proposed that allows for an automatic assessment. On this basis time-dependent stochastic models for the event-discrete description of cooperation situations shall be developed, in order to predict the likely intentions of cooperation partners and to prepare for an optimal behavioral decision, accepted by both the passengers in the car and other road users. Finally, the algorithm shall be implemented within a real-time framework and it will also be demonstrated in a testing vehicle. As an outcome of the observational traffic study a huge database is to be expected, which shall be made available to other research groups.

• DFG Programme: Priority Programmes
• Subproject of: SPP 1835: Kooperativ interagierende Automobile
• Ehemaliger Antragsteller: Professor Dr.-Ing. Fernando Puente León, until 9/2020 (†)