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 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.

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.

7 boxes in a circle which are linked together

Figure 1: Illustration of an ego agent and relevant neighbors.

graphical representation of a car from above

Figure 2: Kinematic single-track vehicle model.

Model-Predictive Obstacle Avoidance

Autonomous obstacle avoidance (OA) in urban driving is achieved by coupling two model-predictive controllers (MPCs) that realize OA constraints with different levels of complexity. The resulting Two-Layer OA-MPC architecture enables efficient and collision-free OA in real time by exploiting linear time-invariant MPC design, mixed-integer programming (MIP) and quadratic programming (QP).


Gratzer, Alexander L., Maximilian M. Broger, Alexander Schirrer, and Stefan Jakubek. "Flatness-Based Mixed-Integer Obstacle Avoidance MPC for Collision-Safe Automated Urban Driving, opens an external URL in a new window." In 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT), pp. 1844-1849. IEEE, 2023.

Gratzer, Alexander L., Alexander Schirrer, and Stefan Jakubek. "Agile Multi-Agent Model Architecture for Intelligent Intersection Traffic Simulation, opens an external URL in a new window." IFAC-PapersOnLine 55, no. 27 (2022): 89-95.

Gratzer, Alexander L., Alexander Schirrer, Elvira Thonhofer, Faruk Pasic, Stefan Jakubek, and C. F. Mecklenbräuker. "Short-Term Collision Estimation by Stochastic Predictions in Multi-Agent Intersection Traffic, opens an external URL in a new window" In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), pp. 1-6. IEEE, 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 window." IEEE Transactions on Intelligent Transportation Systems 23, no. 10 (2022): 19358-19373.


  • October 2020 - February 2024

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Univ.Ass. Dipl.-Ing. Alexander Lukas Gratzer BSc

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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