Intelligent Intersection (IntIntSec)

Project Description

Heavy morning traffic at a large intersection, next to it a school, bike paths, regular buses and a crossing tram – a challenging situation for traffic planning as well as for all road users.

Increasing traffic in inner-city areas aggravates the conflict between safety, traffic efficiency, and environmental pollution. Intersections are critical nodes in traffic networks, which, however, are mostly only controlled via fixed, pre-defined traffic light phase schedules. Inflexible, sub-optimal traffic light control can lead to unnecessary traffic jams and emissions. Individual needs, requirements and possibilities of different road users cannot be considered up to now.

Project Goals

In principle, modern information & communication technologies and control concepts offer the potential to comprehensively manage and optimize intersection traffic in in real time. The requirements of all road users can be considered, the situations can be interpreted in the best possible way and coordinated, cooperative control strategies can be implemented to realize a holistic optimum. Therefore, in this project, novel, integrated and flexible communication, control and simulation methods are to be developed to implement an “intelligent intersection” system that utilizes available real-time information on the positions, speeds and expected behavior of the road users to simultaneously

  • ensure traffic safety for all road users in the context of an intersection,
  • efficiently regulate the flow of traffic, and thus
  • optimize the overall energy consumption and minimize traffic emissions resulting from passing the intersection.
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Multi-Agent Model Architecture for Intersection Traffic Simulation

Urban traffic can naturally be modeled as a distributed and heterogeneous multi- agent dynamic system. To allow a scalable solution for simulation, control, and information management, we developed a simple but powerful generic model architecture that supports various traffic participant types. While the agent actions are restricted to a small set of basic operations, a remarkably rich global system functionality and complex information flow can be modeled. The resulting traffic dynamics and information model enables efficient and parallelizable simulation, control, and prediction computations.


Gratzer, Alexander L., Alexander Schirrer, and Stefan Jakubek. „Agile Multi-Agent Architecture for Intelligent Intersection Traffic Management.” IFAC MS-MoViC (2022).

Gratzer, Alexander L., Alexander Schirrer, Elvira Thonhofer, and Stefan Jakubek. „Short-Term Collision Estimation by Stochastic Predictions in Multi-Agent Intersection Traffic, opens an external URL in a new window”. IEEE ICECET (2022).

Gratzer, Alexander L., Sebastian Thormann, Alexander Schirrer, and Stefan Jakubek. "String Stable and Collision-Safe Model Predictive Platoon Control, opens an external URL in a new windowIEEE Transactions on Intelligent Transportation Systems (2022).


  • October 2020 - October 2023

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Privatdoz. Dipl.-Ing. Dr.techn. Alexander Schirrer

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1st Place at the KFV Research Award 2022!

Text award-winning research project

The FFG research project IntIntSec was awarded first place in the KFV Förderpreis 2022 for its creative and ambitious new solutions for more security in everyday life! » More Info