PrioPoint - Quantification of the effects of dynamic detection points in the prioritization of public transport at traffic lights

© DFG

Project leader: Prof. Dr. Meng Wang

Project duration: 01/2027 - 12/2027 (Explore Phase) 

Short description:

The sustainable transformation of urban mobility requires a shift in the modal split towards environmentally friendly transportation modes, which include public transport (PT), cycling, micromobility, and walking. This development highlights the necessity of prioritizing environmentally friendly transport modes at traffic lights (LSA) when distributing the scarce resource of green time, as opposed to motorized individual and freight transport.

A key aspect of prioritizing public transport vehicles is determining the optimal detection time for the vehicle, which is technically implemented through a specific detection point. While solutions for optimizing traffic flow at traffic lights using V2X technologies already exist, they are associated with high investment costs for the necessary infrastructure, making them challenging for municipalities.

The goal of the PrioPoint project is therefore to investigate whether dynamic signal deteciton points for public transport vehicles could represent a more cost-effective alternative to minimizing delay times for all traffic participants. To achieve this, existing control programs for individual traffic lights will be integrated into a simulation environment. Using real-world measurements of incoming traffic flows, the impact of dynamic detection points on delay times in various traffic scenarios will be analyzed.

The project is being conducted in collaboration with Leipzig’s Office for Mobility and Civil Engineering as well as the Leipzig Transport Authority. During the first phase of the project, which is scheduled to run from January through December 2027, preparations will be made for data provision from a legal, administrative, and technical perspective.

PrioPoint is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project no. 589846560.