Vulnerable Road User Intention Detection for Urban Locations (VRUIDFUL)

• Subject Area: Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 498086453

The VRUIDFUL project is intended to place a clear focus on expanding the previous research work of OTH Amberg-Weiden in the field of mobility to include intelligent infrastructure (e.g., monitoring sensors, advanced traffic light systems). Specifically, their setup in a real urban test field and their integration into an integral safety system for vulnerable road users (VRU) will be researched in several phases: Within the scope of this application, an area in Amberg that is particularly heavily frequented by vulnerable road users (VRU) (around the university, KiTa and kindergarten) is to be equipped with intelligent infrastructure units (IISU). These will be used to collect and evaluate extensive data. The sensor technology in the IISU is based on radar, lidar, thermal imaging and stereo camera, the intelligence in the units aims at the detection and classification of objects, especially VRU and groups of VRU.The obtained abstracted data (3D cubes) are transmitted to a central server by means of mobile radio, ITS-G5 (and partly LoRA), stored and can be used for further analysis. Since only abstracted data is transmitted to the server and stored, data protection compliance is ensured.In parallel, selected traffic light systems in the test area will be equipped with V2x communication units and a connection to the traffic control computer to send out traffic light phases in advance. This information will be time-synchronized and stored on the server. Other data, such as weather conditions, are also recorded so that it is possible to make a well-founded evaluation of the influences of traffic light switching and weather conditions on the behavior of VRUs.Based on the research data, research projects on intention recognition of vulnerable road users and their behavior are to be initiated together with partners (e.g. from the Bavarian AI mobility network "AImotion") in a second phase. The resulting findings are to be used to derive warning strategies and recommended actions for vehicles in order to detect potentially dangerous scenarios (such as pedestrians or cyclists who want to "quickly" cross the street after a longer "green" phase when the pedestrian light turns "red", or pedestrians are inattentively following a crowd of other VRUs) at an early stage and avoid accidents. Effort and benefit are to be evaluated.In a third phase, these warning strategies and recommended actions should be discussed with the stakeholders involved, i.e., traffic planners, vehicle manufacturers, citizens, etc. Initially, a smartphone app, for example, could help increase pedestrian awareness. However, the overall goal would be to make the integral system a reality in joint projects with vehicle manufacturers and traffic planners, i.e., to integrate not only pedestrians but also vehicles into the warning concept.

• DFG Programme: Major Instrumentation Initiatives
• Major Instrumentation: Ampelphasenkommunikation
• Instrumentation Group: 7300 Prozeßperipherie, Datenübertragung (außer 600-699, 720-729, 731-749)
• Applicant Institution: Ostbayerische Technische Hochschule Amberg-Weiden (OTH)
• Leader: Professor Dr.-Ing. Alfred Höß
• Co-Investigators: Professor Dr.-Ing. Andreas Aßmuth; Professor Dr.-Ing. Gerald Pirkl; Mathias Schneider