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Micro-mobility rider models for stochastic traffic safety simulations

The safeguarding of autonomous vehicles with regard to safety is an issue that automobile companies are currently having to deal with. Testing autonomous driving functions in real traffic with performance monitoring and trained operators behind the wheels, so-called field operational tests (FOT), are the most obvious approach, but will no longer be feasible with more complex active safety systems, as accidents and particularly fatal accidents are very rare, besides the danger and ethical aspects of testing such situations. To ensure that autonomous vehicles are at least as safe as human drivers, new strategies are needed to prove safety and reliability. One reasonable approach are Monte Carlo simulations, which, due to the arbitrarily high number of test runs, combinatorically cover a large number of possible scenarios. From this, as in medicine, a randomized controlled trial can be designed, by which a reference is compared with a treatment in order to derive a "before and after impact", including possible side effects. To this end, it is essential to simulate traffic scenarios with the necessary degree of detail, to model potential road users with realistic behavior and to assign meaningful probability distributions to variable parameters, which are "drawn" anew in each test run. These simulated test runs can then be understood as virtual FOT. This work aims to identify the relevant parameters and their causal relationships for micro-mobility riders focusing on the domain safety. Furthermore, a strategy is developed to obtain these parameters and derive stochastic models to describe subpopulations. Especially parameters in critical situations and human error are crucial and need to be modeled adequately, but also pose huge challenges due to limited data and ethical constraints. A micro-mobility model for traffic simulations, including probability distributions for significant parameters and human failure will be developed and implemented. Finally, a use case is defined and an effectiveness analysis of a traffic treatment (eg. V2X) is performed demonstrated using e-scooters.

MITGLIED IM KOLLEG

seit

Betreuer Technische Hochschule Ingolstadt:

Prof. Dr.-Ing. Werner Huber

Leiter CARISSMA Institute of Automated Driving (C-IAD)

Forschungsschwerpunkte:

  • X-in-the-Loop-Testmethoden für automatisiertes Fahren
  • Wirkungsbewertung durch virtuelle Feldtests und Simulation
  • Generische Versuchsfahrzeugplattformen

Betreute Projekte:

Publikationen

Brunner, P., Denk, F., Huber, W., & Kates, R. (2019, October). Virtual safety performance assessment for automated driving in complex urban traffic scenarios. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 679-685). IEEE.

Brunner, P., Löcken, A., Denk, F., Kates, R., & Huber, W. Analysis of experimental data on dynamics and behavior of e-scooter riders and applications to the impact of automated driving functions on urban road safety. In 2020 IEEE Intelligent Vehicles Symposium (IV) (pp. 219-225). IEEE.

Löcken, A., Brunner, P., & Kates, R. (2020, September). Impact of Hand Signals on Safety: Two Controlled Studies With Novice E-Scooter Riders. In 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 132-140).

Pascal Brunner

Pascal Brunner

Technische Hochschule Ingolstadt

Publikationen und Poster

Pascal Brunner, Vikram Singh, Florian Denk, Martin Margreiter, Klaus Bogenberger, Werner Huber, Ronald Kates, 12/2022, Safety impacts of rising urban micromobility: statistical analysis of e-scooter use and risky rider behavior in Ingolstadt, Germany, Santiago, Chile

Florian Denk, Pascal Brunner, Werner Huber, Martin Margreiter, Klaus Bogenberger, Ronald Kates, 10/2022, Assessment of traffic safety interventions using virtual randomized controlled trials: potential of connected and automated driving including V2X for collision reduction at urban intersections, Macau, China, DOI:10.1109/ITSC55140.2022.9921764

Johannes Lindner, Andreas Keler, Georgios Grigoropoulos, Patrick Malcom, Florian Denk, Pascal Brunner, Klaus Bogenberger, 10/2022, A coupled driving simulator to investigate the interaction between bicycles and automated vehicles, Macau, China, DOI:10.1109/ITSC55140.2022.9922400

Johannes Lindner, Georgios Grigoropoulos, Andreas Keler, Patrick Malcom, Florian Denk, Pascal Brunner, Klaus Bogenberger, 06/2022, A mobile application for resolving bicyclist and automated vehicle interactions at intersections, Aachen, Germany, DOI: 10.1109/IV51971.2022.9827439

Pascal Brunner, Tetmar von dem Bussche-Hünnefeld, Florian Denk, Klaus Bogenberger, Werner Huber, Ronald Kates, 01/2022, An E-Scooter Safety Experiment -Design, Methodology and Results, Washington, United States

Brunner Pascal, Löcken Andreas, Denk Florian, Kates Ronald, Huber Werner, 2020, Analysis of experimental data on dynamics and behavior of e-scooter riders and applications to the impact of automated driving functions on urban road safety, IEEE Intelligent Vehicles Symposium (IV), Las Vegas, US

Denk F., Huber W., Brunner P., Kates R., 2020, The role of perceptual failure and degrading processes in urban traffic accidents: a stochastic computational model for virtual experiments, 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece

Keler, Andreas; Denk, Florian; Brunner, Pascal; Grigoropoulos, Georgios; Malcolm, Patrick; Bogenberger, Klaus, 2021, Varying Bicycle Infrastructures - An Interconnected Simulator Study for Inspecting Motorist-Cyclist Conflicts, DSC 2021 - 20th Driving Simulation & Virtual Reality Conference (DSC 2021)

Koordination des Verbundkollegs Mobilität und Verkehr

Treten Sie mit uns in Kontakt. Wir freuen uns auf Ihre Fragen und Anregungen zum Verbundkolleg Mobilität und Verkehr.

Dr. Monika Kolpatzik

Dr. Monika Kolpatzik

Technische Hochschule Ingolstadt
Esplanade 10
85049 Ingolstadt

Telefon: +49 841 93481560
mobilitaet-verkehr.vk@baywiss.de

Marina Schleicher

Marina Schleicher

Technische Hochschule Ingolstadt
Esplanade 10
85049 Ingolstadt

Telefon: +49 841 93483539
mobilitaet-verkehr.vk@baywiss.de