Automated formation of emergency lanes in complex scenarios through intelligent networking (AORTA)

Problem statement

In emergency situations such as traffic accidents and disasters, every second counts. A quickly and correctly formed emergency lane can have a life-saving effect. Rescue service associations estimate that if emergency services arrive four minutes earlier, the chances of survival are increased by up to 40%. However, a correctly and timely formed emergency lane is rare and difficult to implement without the foresight and prudent actions of all road users. Many drivers lack an overview of the situation of all the traffic around them, which is why they often fail to react correctly. As a result, emergency vehicles get stuck in traffic jams and lose valuable time.


Project objective

A consortium of eleven partners: research institutions, public institutions and industry under the leadership of the Technical University of Kaiserslautern is researching and testing the formation of an emergency lane in AORTA based on automation, networking and artificial intelligence (AI) methods.

This is achieved by integrating infrastructure, sensor technology, communication, vehicle technology and display functions, which enable coordinated decision-making levels of various degrees of abstraction from the operations control center to the automated driving maneuver in small or large areas.



A decentralized data platform is being developed on which an artificial intelligence makes decisions for cooperative driving tasks and communicates them to the vehicles. This requires static and dynamic information from connected vehicles, digital road infrastructure and sensors along the route of emergency vehicles. The solution is designed as a compatible extension to existing and future digitalization solutions of vehicle manufacturers and is based on current standards, so that no modification on the vehicle side is necessary to integrate participating vehicles.

Tasks 3D Mapping Solutions

High-precision digital maps of the test fields for use in the digital twin and simulation are created.


Project duration
01/2021 – 06/2023

Project website