In 2018, 25 thousand people lost their lives on European roads and about 135 thousand were seriously injured. This translates to 68 fatalities and 369 injured on average per day. Consequently, increasing traffic safety is among the goals of the European Commission and incorporated in the Sustainable Development Goals. However, it is unclear with which traffic measures this goal can be reached. This is due to the properties of the traffic system: it is composed of a multitude of variable processes which result in countless unique situations we find ourselves in when participating in traffic. Furthermore, accidents are rare events making the generation of necessary evidence a lengthy process. Hence, the effect of a certain measure, both positive and negative, is revealed with enormous time delay. This poses the risk of misdirected resources and further human suffering. A potential solution to provide a priori evidence for the effects of a traffic measure are virtual randomized controlled trials . To this end, real traffic is replaced by simulated traffic that is suitable to generate a relevant and representative sample for assessing traffic safety. Since traffic accidents are often linked to human failure, modelling these processes in a valid way must be a major concern. This PhD project targets to contribute to modelling human failure in traffic. More specifically, driver failures leading to accidents with cyclists in urban right turns will be studied and modelled. In order to demonstrate the proposed assessment method, a system to warn cyclists of a potential conflict based on LiDAR technology will be modelled. In a last step, a virtual experiment with and without the warning system will be conducted to assess the effect of the system.
The role of perceptual failure and degrading processes in urban traffic accidents - a stochastic computational model for virtual experiments
MEMBER IN THE JOINT ACADEMIC PARTNERSHIP
Prof. Dr.-Ing. Klaus Bogenberger
- Verkehrstechnik / Verkehrsmanagement
- Lade- und Mobilitätsverhalten von batterieelektrischen Fahrzeugen und deren Einbindung in das Stromnetz als dezentrale Energiespeicher zur Erbringung von Systemdienstleistung
- HIL Tests zur Infrastrukturgestützen Führung automatisierter Fahrzeuge im urbanen Umfeld
- Emissionsfreier öffentlicher Personennahverkehr
- Micro-mobility rider models for stochastic traffic safety simulations
- The role of perceptual failure and degrading processes in urban traffic accidents - a stochastic computational model for virtual experiments
- Generische Bestimmung des frei befahrbaren Raums für das autonome Fahren durch globale Risikominimierung einer lokalen dynamischen Fahrscene mittels eines prädiktiv-reaktiven Risikoprojektions- und -ausgleichsverfahren
Prof. Dr.-Ing. Werner Huber
Leiter CARISSMA Institute of Automated Driving (C-IAD)
- X-in-the-Loop-Testmethoden für automatisiertes Fahren
- Wirkungsbewertung durch virtuelle Feldtests und Simulation
- Generische Versuchsfahrzeugplattformen
P. Brunner, F. Denk, W. Huber, and R. Kates, “Virtual safety performance assessment for automated driving in complex urban traffic scenarios,” in 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, Oct. 2019, pp. 679–685. doi: 10.1109/ITSC.2019.8917517.
F. Denk, W. Huber, P. Brunner, and R. Kates, “The role of perceptual failure and degrading processes in urban traffic accidents: a stochastic computational model for virtual experiments,” in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece, Sep. 2020, pp. 1–7. doi: 10.1109/ITSC45102.2020.9294498.